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Briefings in Bioinformatics, Volume 25
Volume 25, Number 1, November 2023
- Junjie Zhu, Zhengxin Li, Haowei Tong, Zhouyu Lu, Ningjie Zhang, Ting Wei, Hai-Feng Chen
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Phanto-IDP: compact model for precise intrinsically disordered protein backbone generation and enhanced sampling. - Dong Liu, Biao Zhang, Jun Liu, Hui Li, Le Song, Guijun Zhang
Assessing protein model quality based on deep graph coupled networks using protein language model. - Milos Musil, Andrej Jezik, Jana Horackova
FireProt 2.0: web-based platform for the fully automated design of thermostable proteins. - Francis Yew Fu Tieng
A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools. - Jiawei Zhang, Wang Ma
Accurate TCR-pMHC interaction prediction using a BERT-based transfer learning method. - Miles McGibbon
From intuition to AI: evolution of small molecule representations in drug discovery. - Nhat Truong Pham
Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach. - Wenxuan Xing
iAMP-Attenpred: a novel antimicrobial peptide predictor based on BERT feature extraction method and CNN-BiLSTM-Attention combination model. - Qingyang Yin, Liang Chen:
CellTICS: an explainable neural network for cell-type identification and interpretation based on single-cell RNA-seq data. - Zikun Yang, Basilio Cieza, Dolly Reyes-Dumeyer, Rosa Montesinos, Marcio Soto-Añari, Nilton Custodio
A benchmark study on current GWAS models in admixed populations. - Yajie Meng
Drug repositioning based on weighted local information augmented graph neural network. - Elena Lucy Carter, Chrystala Constantinidou, Mohammad Tauqeer Alam:
Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations. - Ping Fu, Yifan Wu, Zhiyuan Zhang, Ye Qiu, Yirong Wang, Yousong Peng
VIGA: a one-stop tool for eukaryotic virus identification and genome assembly from next-generation-sequencing data. - Yu Mei Wang, Yuzhi Sun, Beiying Wang, Zhiping Wu, Xiao-Ying He
Transfer learning for clustering single-cell RNA-seq data crossing-species and batch, case on uterine fibroids. - Peilong Li
CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation. - Correction to: Breaking the barriers of data scarcity in drug-target affinity prediction.
- Daniel Toro-Domínguez
Response to the letter 'testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis'. - Sang-Ho Yoon
Clustering malignant cell states using universally variable genes. - Jiaxian Yan
Multi-task bioassay pre-training for protein-ligand binding affinity prediction. - Pavel Akhtyamov
scATAC-seq preprocessing and imputation evaluation system for visualization, clustering and digital footprinting. - Jie Dong, Zheng Wu, Huanle Xu, Defang Ouyang
FormulationAI: a novel web-based platform for drug formulation design driven by artificial intelligence. - So-Ra Han
Evidential deep learning for trustworthy prediction of enzyme commission number. - Jorge Beltrán
VirusHound-I: prediction of viral proteins involved in the evasion of host adaptive immune response using the random forest algorithm and generative adversarial network for data augmentation. - Cuiling Wu
A transformer-based genomic prediction method fused with knowledge-guided module. - Min Zou, Honghao Li, Dongqing Su, Yuqiang Xiong, Haodong Wei, Shiyuan Wang, Hongmei Sun, Tao Wang, Qilemuge Xi, Yongchun Zuo
Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes. - Hao Qian, Wenjing Huang, Shikui Tu, Lei Xu:
KGDiff: towards explainable target-aware molecule generation with knowledge guidance. - Jan Stourac, Simeon Borko
PredictONCO: a web tool supporting decision-making in precision oncology by extending the bioinformatics predictions with advanced computing and machine learning. - Lei Chen
RMTLysPTM: recognizing multiple types of lysine PTM sites by deep analysis on sequences. - Zhen-Ning Yin
Unveiling human origins of replication using deep learning: accurate prediction and comprehensive analysis. - Qiyiwen Zhang, Changgee Chang
Robust knowledge-guided biclustering for multi-omics data. - Ruofan Ding, Xudong Zou
xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs. - Qisheng Pan, Stephanie Portelli
Characterization on the oncogenic effect of the missense mutations of p53 via machine learning. - Stavros Makrodimitris
An in-depth comparison of linear and non-linear joint embedding methods for bulk and single-cell multi-omics. - Shuheng Pan
WSGMB: weight signed graph neural network for microbial biomarker identification. - Qilin Wang, Junyou Zhang, Zhaoshuo Liu, Yingying Duan, Chunyan Li
Integrative approaches based on genomic techniques in the functional studies on enhancers. - Fanding Xu
MESPool: Molecular Edge Shrinkage Pooling for hierarchical molecular representation learning and property prediction. - Juntao Li
Identifying phenotype-associated subpopulations through LP_SGL. - Jiahao Zheng
Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering. - Zhen Wang
BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation. - Benzhe Su, Weiwei Wang, Xiaohui Lin
Identifying the potential miRNA biomarkers based on multi-view networks and reinforcement learning for diseases. - Kevin Tippenhauer, Marwin Philips, Carlo R. Largiadèr, Murat Sariyar
Using the PharmCAT tool for Pharmacogenetic clinical decision support.
Volume 25, Number 2, January 2024
- Rajesh Kumar Pathak
Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare. - Fengjuan Huang, Xinjie Fan, Ying Wang, Yu Zou, Jiangfang Lian, Chuang Wang, Feng Ding
Computational insights into the cross-talk between medin and Aβ: implications for age-related vascular risk factors in Alzheimer's disease. - Sheng-Yong Xu
Evaluating the efficacy of MEANGS for mitochondrial genome assembly of cartilaginous and ray-finned fish species. - Minghao Fang, Jingwen Fang, Songwen Luo, Ke Liu, Qiaoni Yu, Jiaxuan Yang, Youyang Zhou, Zongkai Li, Ruoming Sun, Chuang Guo, Kun Qu
eccDNA-pipe: an integrated pipeline for identification, analysis and visualization of extrachromosomal circular DNA from high-throughput sequencing data. - Yi-Heng Zhu, Zi Liu, Yan Liu
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein-DNA binding site prediction. - Hangjia Zhao
labelSeg: segment annotation for tumor copy number alteration profiles. - Simone Maestri
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing. - Ariadna Llop-Peiró
Challenges in distinguishing functional proteins from polyproteins in databases: implications for drug discovery. - Yuyao Zhai, Liang Chen, Minghua Deng
scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq data. - Sowmya Ramaswamy Krishnan
Reliable method for predicting the binding affinity of RNA-small molecule interactions using machine learning. - Wang Xu, Houfang Zhang, Wenhan Guo, Lijun Jiang, Yunjie Zhao
Deciphering principles of nucleosome interactions and impact of cancer-associated mutations from comprehensive interaction network analysis. - Xinyu Guo, Liang Chen
From G1 to M: a comparative study of methods for identifying cell cycle phases. - Musu Yuan, Hui Wan, Zihao Wang, Qirui Guo, Minghua Deng
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data. - Mengting Niu
Identification, characterization and expression analysis of circRNA encoded by SARS-CoV-1 and SARS-CoV-2. - Qiuchen Meng
scDecouple: decoupling cellular response from infected proportion bias in scCRISPR-seq. - Songqi Zhou, Yang Li, Wenyuan Wu, Li Li
scMMT: a multi-use deep learning approach for cell annotation, protein prediction and embedding in single-cell RNA-seq data. - Mona Nourbakhsh, Kristine Degn, Astrid Saksager, Matteo Tiberti, Elena Papaleo:
Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks. - Jiaxuan Liu, Yonggang Lu, Li Zhu:
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction. - Yury A Barbitoff
Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges. - Yaofeng Hu
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics. - Lu-Xiang Guo, Lei Wang
Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations. - Junxiang Zeng, Xiupan Gao, Limei Gao, Youyou Yu, Lisong Shen, Xiujun Pan
Recognition of rare antinuclear antibody patterns based on a novel attention-based enhancement framework. - Merve Vural-Ozdeniz
CAP-RNAseq: an integrated pipeline for functional annotation and prioritization of co-expression clusters. - Lijuan Wang
The landscape of the methodology in drug repurposing using human genomic data: a systematic review. - Min Sun
Enhancing protein dynamics analysis with hydrophilic polyethylene glycol cross-linkers. - Jing Meng
PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network. - Gulam Sarwar Chuwdhury, Yunshan Guo, Chi-Leung Chiang, Ka-On Lam, Ngar-Woon Kam, Zhonghua Liu
ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction. - Yue Guo
SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction. - Giovanni Visonà
Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery. - Céline Brouard
Should we really use graph neural networks for transcriptomic prediction? - Chengcheng Zhang, Tianyi Zang, Tianyi Zhao:
KGE-UNIT: toward the unification of molecular interactions prediction based on knowledge graph and multi-task learning on drug discovery. - Jici Jiang
FEOpti-ACVP: identification of novel anti-coronavirus peptide sequences based on feature engineering and optimization. - Zhen-Hao Guo
scCorrector: a robust method for integrating multi-study single-cell data. - Youngjune Park
Species-agnostic transfer learning for cross-species transcriptomics data integration without gene orthology. - Olivier Cinquin
ChIP-GPT: a managed large language model for robust data extraction from biomedical database records. - Yibo Zhang
On the core segmentation algorithms of copy number variation detection tools. - Yan Miao
VirGrapher: a graph-based viral identifier for long sequences from metagenomes. - Qingyue Wei, Md Tauhidul Islam, Yuyin Zhou, Lei Xing
Self-supervised deep learning of gene-gene interactions for improved gene expression recovery. - Aleksandra E. Badaczewska-Dawid
Structure prediction of linear and cyclic peptides using CABS-flex. - Lingyan Zheng, Shuiyang Shi, Xiuna Sun, Mingkun Lu, Yang Liao, Sisi Zhu, Hongning Zhang
MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics. - Seokjin Han
Standigm ASK™: knowledge graph and artificial intelligence platform applied to target discovery in idiopathic pulmonary fibrosis. - Jin Zhang, Zikang Ma, Yan Yang, Lei Guo, Lei Du
Modeling genotype-protein interaction and correlation for Alzheimer's disease: a multi-omics imaging genetics study. - Shuang Gu, Chaoliang Wen, Zhen Xiao, Qiang Huang, Zheyi Jiang, Honghong Liu, Jia Gao, Junying Li, Congjiao Sun, Ning Yang
MyoV: a deep learning-based tool for the automated quantification of muscle fibers. - Fabio N. de Mello
The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping. - Yue Zang, Xia Ran
Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer. - Zeyu Luo
Interpretable feature extraction and dimensionality reduction in ESM2 for protein localization prediction. - Shi Zhang, Rui Zhang
Reconstructing complex admixture history using a hierarchical model. - Shuo Li, Yan Liu
GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference. - Albert Katchborian-Neto
Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data. - Xiaodi Yang
Multi-modal features-based human-herpesvirus protein-protein interaction prediction by using LightGBM. - Kandarp Joshi
epidecodeR: a functional exploration tool for epigenetic and epitranscriptomic regulation. - Yantong Cai
Deqformer: high-definition and scalable deep learning probe design method. - Jingxuan Qiu, Wanchun Nie
PB-LKS: a python package for predicting phage-bacteria interaction through local K-mer strategy. - Wenyuan Ma
New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges. - Tingpeng Yang
Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.
Volume 25, Number 3, 2024
- Hui Wang, Dong Liu, Kailong Zhao, Yajun Wang, Guijun Zhang
SPDesign: protein sequence designer based on structural sequence profile using ultrafast shape recognition. - Pengyong Li, Zhengxiang Jiang, Tianxiao Liu, Xinyu Liu
Improving drug response prediction via integrating gene relationships with deep learning. - Haoquan Liu, Yunjie Zhao
Integrated modeling of protein and RNA. - Zhenyu Wei
Meta-DHGNN: method for CRS-related cytokines analysis in CAR-T therapy based on meta-learning directed heterogeneous graph neural network. - Junxi Mu, Zhengxin Li, Bo Zhang, Qi Zhang, Jamshed Iqbal, Abdul Wadood, Ting Wei, Yan Feng, Hai-Feng Chen
Graphormer supervised de novo protein design method and function validation. - Seunghyun Wang
Community cohesion looseness in gene networks reveals individualized drug targets and resistance. - Zhen Gao
DeepFGRN: inference of gene regulatory network with regulation type based on directed graph embedding. - Xinyan Wang, Kuo Yang, Ting Jia, Fanghui Gu, Chongyu Wang, Kuan Xu, Zixin Shu, Jianan Xia, Qiang Zhu, Xuezhong Zhou
KDGene: knowledge graph completion for disease gene prediction using interactional tensor decomposition. - Akram Vasighizaker
SEGCECO: Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication. - Zhen Tian
MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy. - Priyotosh Sil
Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph. - Correction to: Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.
- Chen Peng, Qiong Chen, Shangjin Tan, Xiaotao Shen
Generalized reporter score-based enrichment analysis for omics data. - Zhao Peng, Jiaqiang Li, Xingpeng Jiang, Cuihong Wan
sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome. - Takashi Amisaki
Multilevel superposition for deciphering the conformational variability of protein ensembles. - Huanhuan Liu, Qinwei Chen, Jintao Guo, Ying Zhou, Zhiyu You, Jun Ren, Yuanyuan Zeng, Jing Yang, Jialiang Huang
Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues. - Wang Yin
SpatialcoGCN: deconvolution and spatial information-aware simulation of spatial transcriptomics data via deep graph co-embedding. - Xiao-Hong Ding, Yi Xiao, Fenfang Chen, Cheng-Lin Liu, Tong Fu, Zhi-Ming Shao
The HLA-I landscape confers prognosis and antitumor immunity in breast cancer. - Boya Ji, Haitao Zou, Liwen Xu, Xiaolan Xie, Shaoliang Peng
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA-disease associations prediction. - Thomas G. Brooks
BEERS2: RNA-Seq simulation through high fidelity in silico modeling. - Ken Chen
Self-supervised learning on millions of primary RNA sequences from 72 vertebrates improves sequence-based RNA splicing prediction. - Tram Huynh, Zixuan Cang
Topological and geometric analysis of cell states in single-cell transcriptomic data. - Guoxuan Ma
Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes. - Qiuhao Chen, Liyuan Zhang, Yaojia Liu, Zhonghao Qin, Tianyi Zhao
PUTransGCN: identification of piRNA-disease associations based on attention encoding graph convolutional network and positive unlabelled learning. - Correction to: Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics.
- Zechen Wang
A new paradigm for applying deep learning to protein-ligand interaction prediction. - Marc-Antoine Gerault
IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data. - Kongming Li, Jiahao Li, Yuhao Tao, Fei Wang
stDiff: a diffusion model for imputing spatial transcriptomics through single-cell transcriptomics. - Le Zhang
ConvNeXt-MHC: improving MHC-peptide affinity prediction by structure-derived degenerate coding and the ConvNeXt model. - Hongyuan Zhao, Suyi Zhang, Hui Qin, Xiaogang Liu, Dongna Ma
DSNetax: a deep learning species annotation method based on a deep-shallow parallel framework. - Tinghe Zhang
Understanding YTHDF2-mediated mRNA degradation by m6A-BERT-Deg. - Weihang Zhang, Yang Cui
HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data. - Theinmozhi Arulraj
Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology. - Ming-Siang Huang, Jen-Chieh Han, Pei-Yen Lin, Yu-Ting You, Richard Tzong-Han Tsai
Surveying biomedical relation extraction: a critical examination of current datasets and the proposal of a new resource. - Meng Wang, Chuqi Lei, Jianxin Wang
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. - Danel Olaverri-Mendizabal
Review and meta-analysis of the genetic Minimal Cut Set approach for gene essentiality prediction in cancer metabolism. - Correction to: Inflated false discovery rate due to volcano plots: problem and solutions.
- Lixin Lei, Kaitai Han, Zijun Wang, Chaojing Shi
Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics. - Yue Kang, Hongyu Zhang, Jinting Guan
scINRB: single-cell gene expression imputation with network regularization and bulk RNA-seq data. - Jinze Huang, Yang Zhao
SEAOP: a statistical ensemble approach for outlier detection in quantitative proteomics data. - Mingshuai Chen, Mingai Sun, Xi Su, Prayag Tiwari
Fuzzy kernel evidence Random Forest for identifying pseudouridine sites. - Correction to: DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences.
- Adam Wright
FAIR Header Reference genome: a TRUSTworthy standard. - Zhanyu Xu, Haibo Liao, Liuliu Huang, Qingfeng Chen
IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability. - Chunjiang Yu, Hui Zong, Yalan Chen, Yibin Zhou, Xingyun Liu, Yuxin Lin, Jiakun Li, Xiaonan Zheng, Hua Min, Bairong Shen
PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data. - Xing Chen
Computational model for drug research. - Zhaojia Chen, Noor ul Ain
From tradition to innovation: conventional and deep learning frameworks in genome annotation. - Conghao Wang
GLDM: hit molecule generation with constrained graph latent diffusion model. - Shenjie Wang, Xiaoyan Zhu, Xuwen Wang, Yuqian Liu, Minchao Zhao, Zhili Chang, Xiaonan Wang, Yang Shao, Jiayin Wang
TMBstable: a variant caller controls performance variation across heterogeneous sequencing samples.
Volume 25, Number 4, 2024
- Simin Xia
Integration of protein sequence and protein-protein interaction data by hypergraph learning to identify novel protein complexes. - Eduardo N. Castanho, Helena Aidos, Sara C. Madeira
Biclustering data analysis: a comprehensive survey. - Qiaosi Tang
Morphological profiling for drug discovery in the era of deep learning. - Ran Jia, Ying-Zan Ren, Po-Nian Li, Rui Gao
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition. - Yanli Wang, Jianlin Cheng
HiCDiff: single-cell Hi-C data denoising with diffusion models. - Lequn Wang
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics. - Sudipto Baul, Khandakar Tanvir Ahmed, Qibing Jiang, Guangyu Wang, Qian Li, Jeongsik Yong
Integrating spatial transcriptomics and bulk RNA-seq: predicting gene expression with enhanced resolution through graph attention networks. - Chengshang Lyu
Detecting tipping points of complex diseases by network information entropy. - Yue Li
Image-based molecular representation learning for drug development: a survey. - Bijia Chen, Chao Ren, Zhangyi Ouyang, Jingxuan Xu, Kang Xu, Yaru Li, Hejiang Guo, Xuemei Bai, Mengge Tian, Xiang Xu
Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair. - Hongtai Jing, Zhengtao Gao, Sheng Xu
Accurate prediction of antibody function and structure using bio-inspired antibody language model. - Georg Hahn, Dmitry Prokopenko, Julian Hecker
Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data. - Guoqiang Zhou, Yuke Qin, Qiansen Hong, Haoran Li
GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction. - Sarthak Jain, Sandra E. Safo
DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification. - Qingxiong Tan, Jin Xiao
ifDEEPre: large protein language-based deep learning enables interpretable and fast predictions of enzyme commission numbers. - Lixin Ren
Predicting RNA polymerase II transcriptional elongation pausing and associated histone code. - Skylar A Gay
Phylogenetic inference of inter-population transmission rates for infectious diseases. - Qiang Yang
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses. - Ru Zhang, Yanmei Lin, Yijia Wu, Lei Deng
MvMRL: a multi-view molecular representation learning method for molecular property prediction. - Feng Jiang
GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity. - Joshua Beals, Haiyan Hu, Xiaoman Li
A survey of experimental and computational identification of small proteins. - Xiangru Tang
A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation. - Lei Li
A hybrid demultiplexing strategy that improves performance and robustness of cell hashing. - Zhihao Si, Hanshuang Li, Wenjing Shang, Yanan Zhao, Lingjiao Kong, Chunshen Long, Yongchun Zuo
SpaNCMG: improving spatial domains identification of spatial transcriptomics using neighborhood-complementary mixed-view graph convolutional network. - Ao Shen
Complementary multi-modality molecular self-supervised learning via non-overlapping masking for property prediction. - Haiping Zhang
Revolutionizing GPCR-ligand predictions: DeepGPCR with experimental validation for high-precision drug discovery. - Jun Teng, Tingting Zhai, Xinyi Zhang, Changheng Zhao, Wenwen Wang, Hui Tang, Dan Wang, Yingli Shang, Chao Ning
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information. - Steven Allers, Kyle A. O'Connell, Thad B. Carlson, David Belardo, Benjamin L. King
Reusable tutorials for using cloud-based computing environments for the analysis of bacterial gene expression data from bulk RNA sequencing. - Md. Mamunur Rashid
Advancing drug-response prediction using multi-modal and -omics machine learning integration (MOMLIN): a case study on breast cancer clinical data. - Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model.
- Jing-Tian Wang
FastBiCmrMLM: a fast and powerful compressed variance component mixed logistic model for big genomic case-control genome-wide association study. - Alen Suljic
Efficient SARS-CoV-2 variant detection and monitoring with Spike Screen next-generation sequencing. - Zhengfa Xue, Aifen Zhou, Xiaoyan Zhu, Linxuan Li, Huanhuan Zhu, Xin Jin, Jiayin Wang
NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach. - Jiashuo Wu
IDMIR: identification of dysregulated miRNAs associated with disease based on a miRNA-miRNA interaction network constructed through gene expression data. - Siwen Wu, Jun-tao Guo
Improved prediction of DNA and RNA binding proteins with deep learning models. - Christophe Boetto
MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data. - Junyao Jiang
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data. - Shengbo Wu
Multi-omic analysis tools for microbial metabolites prediction. - Jacob J. E. Koopman
From machine learning to clinical practice: phenotypic clusters of anti-MDA5 antibody-positive dermatomyositis. - Jilong Bian, Hao Lu, Guanghui Dong, Guohua Wang:
Hierarchical multimodal self-attention-based graph neural network for DTI prediction. - Pi-Jing Wei, Ziqiang Guo
Inference of gene regulatory networks based on directed graph convolutional networks. - Qirui Guo, Musu Yuan, Lei Zhang, Minghua Deng
scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement. - Liang Cheng
Attention mechanism models for precision medicine. - Euiseong Ko
SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis. - Weibing Wang, Yusen Ye, Lin Gao
Statistical modeling and significance estimation of multi-way chromatin contacts with HyperloopFinder. - Baohui Lin
A comprehensive review and comparison of existing computational methods for protein function prediction. - Emily McLeish, Nataliya Slater, Frank L. Mastaglia, Merrilee Needham
Balancing Clinical Applicability and Scientific Depth in ML Models for MDA5-DM Prognosis. - Yujin Kim, Minwoo Jeong, In Gyeong Koh, Chanhee Kim, Hyeji Lee, Jae Hyun Kim, Ronald Yurko
CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data. - Mengxin Zheng
EGPDI: identifying protein-DNA binding sites based on multi-view graph embedding fusion. - Jaeyoon Kim
ctGAN: combined transformation of gene expression and survival data with generative adversarial network. - Zihan Dong
LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information. - Xinjia Ruan
PIPET: predicting relevant subpopulations in single-cell data using phenotypic information from bulk data. - Heng Hu
SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies. - Ryan P. Seaman, Ross Campbell, Valena Doe, Zelaikha Yosufzai, Joel H. Graber
A cloud-based training module for efficient de novo transcriptome assembly using Nextflow and Google cloud. - Sara Joubbi, Alessio Micheli, Paolo Milazzo, Giuseppe Maccari, Giorgio Ciano, Dario Cardamone, Duccio Medini:
Antibody design using deep learning: from sequence and structure design to affinity maturation. - Regina Nóra Fiam, Csabai István, Solymosi Norbert
Comparing full variation profile analysis with the conventional consensus method in SARS-CoV-2 phylogeny. - Ali H. Rafati
Approaches to embryonic neurodevelopment: from neural cell to neural tube formation through mathematical models. - Han Wang, Chang Li, Xinyu Yu, Jingyang Gao:
Deletion variants calling in third-generation sequencing data based on a dual-attention mechanism. - Paolo Battuello, Giorgio Corti, Alice Bartolini, Annalisa Lorenzato, Alberto Sogari, Mariangela Russo, Federica Di Nicolantonio, Alberto Bardelli, Giovanni Crisafulli
Mutational signatures of colorectal cancers according to distinct computational workflows. - Hwiyoung Lee
dCCA: detecting differential covariation patterns between two types of high-throughput omics data. - Maria A Rujano, Jan-Willem Boiten
Sharing sensitive data in life sciences: an overview of centralized and federated approaches. - Sandeep Singh
RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data. - Asif M. Khan
A global initiative on addressing bioinformatics' grand challenges. - Zeqian Li, Shilong Wang, Hai Cui, Xiaoxia Liu, Yijia Zhang
Spatiotemporal constrained RNA-protein heterogeneous network for protein complex identification. - Meihui Tian, Weifang Sun, Yinhui Mao, Yanan Zhang, Huan Liu, Yong Tang
Mechanistic study of acupuncture on the pterygopalatine ganglion to improve allergic rhinitis: analysis of multi-target effects based on bioinformatics/network topology strategie. - Ishtiaque Ahammad
AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature. - Catalina Gonzalez Gomez
Optimizing in silico drug discovery: simulation of connected differential expression signatures and applications to benchmarking. - Yuan Gao, Bin Ma, Qianshuai Xu, Yuna Peng, Huimin Gong, Aohan Guan, Kexin Hua, Paul R. Langford, Hui Jin
Spatial proximity and gene function: a new dimension in prokaryotic gene association network analysis with 3D-GeneNet. - Juok Cho, Bukyung Baik
Characterizing efficient feature selection for single-cell expression analysis. - Michal Zawisza-Álvarez, Jesús Peñuela-Melero, Esteban Vegas, Ferran Reverter, Jordi Garcia-Fernàndez, Carlos Herrera-Úbeda
Exploring functional conservation in silico: a new machine learning approach to RNA-editing. - En-Yu Lai
Identifying pleiotropic genes via the composite test amidst the complexity of polygenic traits. - Sagar Gupta, Veerbhan Kesarwani, Umesh Bhati, Jyoti, Ravi Shankar
PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants. - Lei Zhang
A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data. - Rajan Gyawali
CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net. - Mostafa Herajy, Fei Liu
Design patterns for the construction of computational biological models. - Quyuan Tao
Benchmarking mapping algorithms for cell-type annotating in mouse brain by integrating single-nucleus RNA-seq and Stereo-seq data. - Alexei Novoloaca
Comparative analysis of integrative classification methods for multi-omics data. - Junbo Duan, Xinrui Zhao, Xiaoming Wu:
LoRA-TV: read depth profile-based clustering of tumor cells in single-cell sequencing. - Nanjun Chen
TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation. - Guoqing Zhang, Hui Wang, Zhiguo Zhang, Lu Zhang
Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework. - Hegang Chen
Comprehensive single-cell RNA-seq analysis using deep interpretable generative modeling guided by biological hierarchy knowledge. - Tao Wang, Han Shu, Jialu Hu
Accurately deciphering spatial domains for spatially resolved transcriptomics with stCluster. - Yahui Lei, Xiao-Tai Huang
DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations. - Aleksandr Ianevski
RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies. - Correction to: Prediction of protein-ligand binding affinity via deep learning models.
- Yue Xi, Kun Zheng
Themis: advancing precision oncology through comprehensive molecular subtyping and optimization. - Bowen Li, Zhen Wang
DrugMetric: quantitative drug-likeness scoring based on chemical space distance. - Miguel Hernandez-Gamarra
CARTAR: a comprehensive web tool for identifying potential targets in chimeric antigen receptor therapies using TCGA and GTEx data. - Dezhen Zhang, Shuhua Gao, Zhi-Ping Liu
LogicGep: Boolean networks inference using symbolic regression from time-series transcriptomic profiling data. - Leandro A Bugnon
sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure. - Guangyu Li
Predicting functional UTR variants by integrating region-specific features. - Lea Eckhart
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction. - Chuiqin Fan, Fuyi Chen, Yuanguo Chen, Liangping Huang, Manna Wang, Yulin Liu, Yu Wang, Huijie Guo, Nanpeng Zheng, Yanbing Liu, Hongwu Wang, Lian Ma
irGSEA: the integration of single-cell rank-based gene set enrichment analysis. - Ruofan Jin, Qing Ye
AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences. - Renmao Tian
PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning. - Gregory Tong, Nasun Hah, Thomas F. Martinez
Comparison of software packages for detecting unannotated translated small open reading frames by Ribo-seq. - Raghvendra Mall
VISH-Pred: an ensemble of fine-tuned ESM models for protein toxicity prediction. - Wenkai Xiang
Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining. - Cheng Zhu
GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach. - Montserrat Goles
Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides. - Runzhou Yu
Utilizing profile hidden Markov model databases for discovering viruses from metagenomic data: a comprehensive review. - Onder Tutsoy
A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing data.
Volume 25, Number 5, 2024
- Aishwarya Budhkar, Ziyang Tang, Xiang Liu, Xuhong Zhang
xSiGra: explainable model for single-cell spatial data elucidation. - Linlin Hou
Attribute-guided prototype network for few-shot molecular property prediction. - Qitao Jia, Yuanling Xia, Fanglin Dong, Weihua Li
MetaFluAD: meta-learning for predicting antigenic distances among influenza viruses. - Wentao Cui
Refining computational inference of gene regulatory networks: integrating knockout data within a multi-task framework. - Zeyu Lu
Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets. - Xinze Liu
Integrated multi-omics with machine learning to uncover the intricacies of kidney disease. - Lei Chen
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs. - Yida Wu, Da Zhou
Reconstruction of gene regulatory networks for Caenorhabditis elegans using tree-shaped gene expression data. - Kerstin Lenhof
Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer. - Fenglei Li
DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras. - Yang Xu, Yuxiang Zhang, Yanru Cui, Kai Zhou, Guangning Yu, Wenyan Yang, Xin Wang, Furong Li, Xiusheng Guan, Xuecai Zhang, Zefeng Yang, Shizhong Xu, Chenwu Xu
GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection. - Weihong Huang, Feng Yang, Qiang Zhang
A dual-scale fused hypergraph convolution-based hyperedge prediction model for predicting missing reactions in genome-scale metabolic networks. - Katarzyna Nalecz-Charkiewicz, Kamil Charkiewicz, Robert M. Nowak:
Quantum computing in bioinformatics: a systematic review mapping. - Marwan Abdellah
Synthesis of geometrically realistic and watertight neuronal ultrastructure manifolds for in silico modeling. - Harrison Anthony
Performance assessment of computational tools to detect microsatellite instability. - Yiran Huang
GloEC: a hierarchical-aware global model for predicting enzyme function. - Xinglong Wang, Kangjie Xu, Xuan Zeng, Kai Linghu, Beichen Zhao, Shangyang Yu, Kun Wang, Shuyao Yu, Xinyi Zhao, Weizhu Zeng, Kai Wang
Machine learning-assisted substrate binding pocket engineering based on structural information. - Weining Lu, Yin Tang, Yu Liu, Shiyi Lin, Qifan Shuai, Bin Liang, Rongqing Zhang
CatLearning: highly accurate gene expression prediction from histone mark. - Benjamin Tam, Philip Naderev P. Lagniton, Mariano Da Luz, Bojin Zhao, Siddharth Sinha, Chon Lok Lei
Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability. - Zhaohan Meng
Heterogeneous biomedical entity representation learning for gene-disease association prediction. - Shunjie Zhang, Pan Li, Shenghan Wang, Jijun Zhu, Zhongting Huang, Fuqiang Cai, Sebastian Freidel, Fei Ling, Emanuel Schwarz
BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data. - Noura Aherrahrou, Hamid Tairi, Zouhair Aherrahrou
Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision. - Xinhao Yi, Siwei Liu, Yu Wu, Douglas McCloskey, Zaiqiao Meng:
BPP: a platform for automatic biochemical pathway prediction. - James S. L. Browning Jr.
Evolutionary algorithms simulating molecular evolution: a new field proposal. - Yan Miao
DeePhafier: a phage lifestyle classifier using a multilayer self-attention neural network combining protein information. - Vijini Mallawaarachchi
Solving genomic puzzles: computational methods for metagenomic binning. - Correction to: Accurate prediction of antibody function and structure using bio-inspired antibody language model.
- Yuxing Wang, Junhan Zhao
A systematic evaluation of computational methods for cell segmentation. - Ruohan Ren, Hongyu Yu, Jiahao Teng, Sihui Mao, Zixuan Bian, Yangtianze Tao, Stephen S.-T. Yau:
CAPE: a deep learning framework with Chaos-Attention net for Promoter Evolution. - Zhenze Liu
scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data. - Liang Liu
A pan-cancer interrogation of intronic polyadenylation and its association with cancer characteristics. - Keyun Zhu, Mengting Huang, Yimeng Wang, Yaxin Gu, Weihua Li, Guixia Liu
MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering. - Chang Dou, Yijie Yang, Fei Zhu, Bingzhi Li, Yuping Duan:
Explorer: efficient DNA coding by De Bruijn graph toward arbitrary local and global biochemical constraints. - Yuefan Lin, Zixiang Pan, Yuansong Zeng, Yuedong Yang
Detecting novel cell type in single-cell chromatin accessibility data via open-set domain adaptation. - Suronjit Kumar Roy, Mohammad Shahangir Biswas
A computational approach to developing a multi-epitope vaccine for combating Pseudomonas aeruginosa-induced pneumonia and sepsis. - Xiaobao Ding, Lin Zhang, Ming Fan
TME-NET: an interpretable deep neural network for predicting pan-cancer immune checkpoint inhibitor responses. - Yinyin Wang
Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study. - Margarita Pertseva
TCR clustering by contrastive learning on antigen specificity. - Jingjing Wang
MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction. - Young Su Ko
TUnA: an uncertainty-aware transformer model for sequence-based protein-protein interaction prediction. - Yang Li, Anjun Ma
Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data. - Feng Li, Jingwen Wang, Mengyue Li, Xiaomeng Zhang, Yongjuan Tang, Xinyu Song, Yifang Zhang, Liying Pei, Jiaqi Liu, Chunlong Zhang
Identifying cell type-specific transcription factor-mediated activity immune modules reveal implications for immunotherapy and molecular classification of pan-cancer. - Qiqing Fu, Chenyu Dong, Yunhe Liu
A comparison of scRNA-seq annotation methods based on experimentally labeled immune cell subtype dataset. - Correction to: Revolutionizing GPCR-ligand predictions: DeepGPCR with experimental validation for high-precision drug discovery.
Volume 25, Number 6, 2024
- Yabin Kuang
DrugDoctor: enhancing drug recommendation in cold-start scenario via visit-level representation learning and training. - Aliaa E. Ali
Atomistic simulations reveal impacts of missense mutations on the structure and function of SynGAP1. - Musaddiq K. Lodi, Anna Chernikov, Preetam Ghosh
COFFEE: consensus single cell-type specific inference for gene regulatory networks. - Jessica Butts, Leif Verace, Christine Wendt, Russel P. Bowler, Craig P. Hersh, Qi Long, Lynn E. Eberly, Sandra E. Safo:
HIP: a method for high-dimensional multi-view data integration and prediction accounting for subgroup heterogeneity. - Michael Y. Fatemi, Yunrui Lu, Alos Diallo
An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology. - Wen Wen, Jiaxin Zhong, Zhaoxi Zhang, Lijuan Jia, Tinyi Chu, Nating Wang, Charles G. Danko, Zhong Wang:
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility. - Yike Shen, Arce Domingo-Relloso, Allison Kupsco, Marianthi-Anna Kioumourtzoglou, Maria Tellez-Plaza, Jason G. Umans, Amanda M. Fretts, Ying Zhang, Peter F. Schnatz, Ramon Casanova, Lisa Warsinger Martin, Steve Horvath, JoAnn E. Manson, Shelley A Cole, Haotian Wu, Eric A Whitsel, Andrea A. Baccarelli, Ana Navas-Acien, Feng Gao
AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease. - Yanghong Guo, Bencong Zhu, Chen Tang, Ruichen Rong, Ying Ma, Guanghua Xiao, Lin Xu
BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data. - Leqi Tian, Jiashun Xiao, Tianwei Yu:
A robust statistical approach for finding informative spatially associated pathways. - Yao Yao, Youhua Frank Chen, Qingpeng Zhang
Optimized patient-specific immune checkpoint inhibitor therapies for cancer treatment based on tumor immune microenvironment modeling. - Kai Shi
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework. - Giulia Russo, Elena Crispino, Silvia Casati, Emanuela Corsini, Andrew Worth, Francesco Pappalardo
Pioneering bioinformatics with agent-based modelling: an innovative protocol to accurately forecast skin or respiratory allergic reactions to chemical sensitizers. - Zhengzheng Lou, Xiaojiao Wei, Yuanhao Hu, Shizhe Hu, Yucong Wu, Zhen Tian:
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy. - Yourui Han, Bolin Chen, Jun Bian, Ruiming Kang, Xuequn Shang:
Cancerous time estimation for interpreting the evolution of lung adenocarcinoma. - Zuqi Li, Sonja Katz, Edoardo Saccenti, David W. Fardo, Peter Claes, Vítor A. P. Martins dos Santos, Kristel Van Steen, Gennady V. Roshchupkin:
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping. - Shisheng Wang
DEWNA: dynamic entropy weight network analysis and its application to the DNA-binding proteome in A549 cells with cisplatin-induced damage. - Sheng Liu, Hye Seung Nam, Ziyu Zeng, Xuehong Deng, Elnaz Pashaei, Yong Zang, Lei Yang, Chenglong Li, Jiaoti Huang, Michael K. Wendt, Xin Lu, Rong Huang, Jun Wan
CDHu40: a novel marker gene set of neuroendocrine prostate cancer. - Guo Wei, Nannan Wu, Kunyang Zhao, Sihai Yang, Long Wang
DeepCheck: multitask learning aids in assessing microbial genome quality. - Marco Ruscone, Andrea Checcoli, Randy W. Heiland, Emmanuel Barillot, Paul Macklin, Laurence Calzone, Vincent Noël:
Building multiscale models with PhysiBoSS, an agent-based modeling tool. - Zhen Wang
AptaDiff: de novo design and optimization of aptamers based on diffusion models. - Anchen Sun, Elizabeth J. Franzmann, Zhibin Chen, Xiaodong Cai:
Deep contrastive learning for predicting cancer prognosis using gene expression values. - Boyi Yu
m6ATM: a deep learning framework for demystifying the m6A epitranscriptome with Nanopore long-read RNA-seq data. - Elena Domínguez Romero
Making PBPK models more reproducible in practice. - Thomas Konstantinovsky, Ayelet Peres, Pazit Polak, Gur Yaari:
An unbiased comparison of immunoglobulin sequence aligners. - Felipe Campelo
Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses. - Xin-Fei Wang
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers. - Lan Huang, Xin-Fei Wang
A multi-task prediction method based on neighborhood structure embedding and signed graph representation learning to infer the relationship between circRNA, miRNA, and cancer. - Sisi Shao
A review of feature selection strategies utilizing graph data structures and Knowledge Graphs. - Limuxuan He
Adversarial regularized autoencoder graph neural network for microbe-disease associations prediction. - Bo Li
Gene expression prediction from histology images via hypergraph neural networks. - Rebecca Ting Jiin Loo
Bioinformatics approaches for studying molecular sex differences in complex diseases. - Yumiao Gao
AntigenBoost: enhanced mRNA-based antigen expression through rational amino acid substitution. - Wenyu Zhang
Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization. - Haochen Ning, Ian Boyes, Ibrahim Numanagic
Diagnostics of viral infections using high-throughput genome sequencing data. - Simone Rancati
Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders. - Lonneke Scheffer
Predictability of antigen binding based on short motifs in the antibody CDRH3. - Laiyi Fu
ACLNDA: an asymmetric graph contrastive learning framework for predicting noncoding RNA-disease associations in heterogeneous graphs. - Gulshan Kumar Sharma, Rakesh Sharma, Kavita Joshi, Sameer Qureshi, Shubhita Mathur, Sharad Sinha, Samit Chatterjee, Vandana Nunia
Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection. - Fang Yang, Chaoqun Li, Wanting Yang, Yumei He, Liping Wu, Kui Jiang, Chao Sun
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis. - Lucas Kook, Anton Rask Lundborg:
Algorithm-agnostic significance testing in supervised learning with multimodal data. - Linjie Wang
nsDCC: dual-level contrastive clustering with nonuniform sampling for scRNA-seq data analysis. - Pablo Perdomo-Quinteiro
Knowledge Graphs for drug repurposing: a review of databases and methods. - Tianxiang Liu, Cangzhi Jia
scDFN: enhancing single-cell RNA-seq clustering with deep fusion networks. - Anjana Kushwaha, Patrice Duroux, Véronique Giudicelli, Konstantin Todorov, Sofia Kossida:
IMGT/RobustpMHC: robust training for class-I MHC peptide binding prediction. - Peng Ran, Yunzhi Wang, Kai Li, Shiman He, Subei Tan, Jiacheng Lv, Jiajun Zhu, Shaoshuai Tang, Jinwen Feng, Zhaoyu Qin, Yan Li, Lin Huang, Yanan Yin, Lingli Zhu, Wenjun Yang, Chen Ding
STAVER: a standardized benchmark dataset-based algorithm for effective variation reduction in large-scale DIA-MS data. - Wei Liu
SpaGIC: graph-informed clustering in spatial transcriptomics via self-supervised contrastive learning. - André Borges Farias
Predicting bacterial transcription factor binding sites through machine learning and structural characterization based on DNA duplex stability. - Zhiwei Rong
Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism. - Sarah Samorodnitsky, Michael C. Wu:
Statistical analysis of multiple regions-of-interest in multiplexed spatial proteomics data. - Haoyang Zhang, Sha Liu, Bingxin Li, Xionghui Zhou
IPFMC: an iterative pathway fusion approach for enhanced multi-omics clustering in cancer research. - Zhaohui Qin
Current computational tools for protein lysine acylation site prediction. - Yipeng Zhang, Cong Shen, Kelin Xia:
Multi-Cover Persistence (MCP)-based machine learning for polymer property prediction. - Dayu Hu, Renxiang Guan, Ke Liang, Hao Yu, Hao Quan, Yawei Zhao, Xinwang Liu, Kunlun He:
scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data. - Tongqing Wei
DeepPBI-KG: a deep learning method for the prediction of phage-bacteria interactions based on key genes. - Yunwei Zhang
Robust variable selection methods with Cox model - a selective practical benchmark study. - Matthijs Vynck
Digital PCR threshold robustness analysis and optimization using dipcensR. - Harvard Wai Hann Hui
Thinking points for effective batch correction on biomedical data. - Quang-Huy Nguyen, Ha Nguyen, Edwin C. Oh, Tin Nguyen:
Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review. - Tianyi Chen, Xindian Wei, Lianxin Xie, Yunfei Zhang, Cheng Liu, Wenjun Shen, Si Wu, Hau-San Wong:
SELF-Former: multi-scale gene filtration transformer for single-cell spatial reconstruction. - Jia Mi
GGN-GO: geometric graph networks for predicting protein function by multi-scale structure features. - Zhenqiu Shu, Min Xia, Kaiwen Tan, Yongbing Zhang, Zhengtao Yu:
Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering. - Rongzhuo Long
siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis. - Xiaoxiu Tan, Feng Xue, Chenhong Zhang, Tao Wang
mbDriver: identifying driver microbes in microbial communities based on time-series microbiome data. - Qiule Yu, Zhixing Zhang, Guixia Liu
ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information. - Yetong Zhou, Shengming Zhou, Yue Bi, Quan Zou
A two-task predictor for discovering phase separation proteins and their undergoing mechanism. - Wei Zhang
Identifying cell types by lasso-constraint regularized Gaussian graphical model based on weighted distance penalty. - Xueping Zhou, Manqi Cai, Molin Yue, Juan C. Celedón, Jiebiao Wang, Ying Ding, Wei Chen, Yanming Li:
Molecular group and correlation guided structural learning for multi-phenotype prediction. - Correction to: Structure prediction of linear and cyclic peptides using CABS-flex.
- Xiang Lin, Siqi Jiang, Le Gao, Zhi Wei
MultiSC: a deep learning pipeline for analyzing multiomics single-cell data. - Qiang Su
Enhancing RNA-seq analysis by addressing all co-existing biases using a self-benchmarking approach with 2D structural insights. - Xiuyu Jiang
DGCL: dual-graph neural networks contrastive learning for molecular property prediction. - Jing Chen, Ran Tao, Yi Qiu, Qun Yuan:
CMFHMDA: a prediction framework for human disease-microbe associations based on cross-domain matrix factorization. - Jiajing Xie, Yuhang Song, Hailong Zheng
PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation. - Yun Zuo
MSlocPRED: deep transfer learning-based identification of multi-label mRNA subcellular localization. - Chaorui Yan, Aoyun Geng, Zhuoyu Pan, Zilong Zhang, Feifei Cui
MultiFeatVotPIP: a voting-based ensemble learning framework for predicting proinflammatory peptides. - Wenwen Min, Zhiceng Shi, Jun Zhang, Jun Wan, Changmiao Wang:
Multimodal contrastive learning for spatial gene expression prediction using histology images. - Xin-Fei Wang
Multi-view learning framework for predicting unknown types of cancer markers via directed graph neural networks fitting regulatory networks. - Zhenhao Zhang, Yuxi Liu, Meichen Xiao, Kun Wang, Yu Huang, Jiang Bian, Ruolin Yang, Fuyi Li:
Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis. - Gaoqi He
Prototype-based contrastive substructure identification for molecular property prediction. - Liuyang Zhao, Landu Jiang, Yufeng Xie, Jianhao Huang, Haoran Xie, Jun Tian, Dian Zhang:
scDTL: enhancing single-cell RNA-seq imputation through deep transfer learning with bulk cell information. - Zhenhua Yu
scTCA: a hybrid Transformer-CNN architecture for imputation and denoising of scDNA-seq data. - Shunjie Chen, Pei Wang
Deciphering gene expression patterns using large-scale transcriptomic data and its applications. - David Seong
Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models. - Sascha Jung, Céline Barlier, Aitor Martinez Perez
Detecting expressed genes in cell populations at the single-cell level with scGeneXpress. - Siding Chen
Predicting functional outcome in ischemic stroke patients using genetic, environmental, and clinical factors: a machine learning analysis of population-based prospective cohort study. - Miao Cui
miniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data. - Ziyi Wang, Peng Luo, Mingming Xiao, Boyang Wang, Tianyu Liu, Xiangyu Sun:
Recover then aggregate: unified cross-modal deep clustering with global structural information for single-cell data. - Yidan Cui, Qingmin Lin, Xin Yuan, Fan Jiang, Shiyang Ma, Zhangsheng Yu:
Mediation analysis in longitudinal study with high-dimensional methylation mediators. - Zilin Ren
NASTRA: accurate analysis of short tandem repeat markers by nanopore sequencing with repeat-structure-aware algorithm. - Chonghui Liu
DrugReSC: targeting disease-critical cell subpopulations with single-cell transcriptomic data for drug repurposing in cancer. - Zachary D. Wallen
A consensus-based classification workflow to determine genetically inferred ancestry from comprehensive genomic profiling of patients with solid tumors. - Mengqiu Zheng, Shaofeng Lin
MetaDegron: multimodal feature-integrated protein language model for predicting E3 ligase targeted degrons. - Qing Li
Progress and opportunities of foundation models in bioinformatics. - Xun Zhang, Kun Qian, Hongwei Li
Structure-preserved integration of scRNA-seq data using heterogeneous graph neural network. - Rongbo Shen, Meiling Cheng, Wencang Wang, Qi Fan, Huan Yan, Jiayue Wen, Zhiyuan Yuan, Jianhua Yao, Yixue Li, Jiao Yuan
Graph domain adaptation-based framework for gene expression enhancement and cell type identification in large-scale spatially resolved transcriptomics. - Qi Dai, Hu Chen
Precision DNA methylation typing via hierarchical clustering of Nanopore current signals and attention-based neural network. - Qi Wang, Bolei Zhang, Yue Guo, Luyu Gong, Erguang Li, Jingping Yang
Unlocking cross-modal interplay of single-cell joint profiling with CellMATE. - Hilbert Yuen In Lam
Protein language models are performant in structure-free virtual screening. - Francesco Tabaro
3t-seq: automatic gene expression analysis of single-copy genes, transposable elements, and tRNAs from RNA-seq data. - Yi Xie
scPanel: a tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets. - Yuchuan Zhang
MLSNet: a deep learning model for predicting transcription factor binding sites. - Junxin Li, Linbu Liao, Chao Zhang, Kaifang Huang, Pengfei Zhang, John Z. H. Zhang
Development and experimental validation of computational methods for human antibody affinity enhancement. - Zhen Wang, Yanhua Fang, Ruoyu Wang, Liwen Kong, Shanshan Liang
Reconstructing tumor clonal heterogeneity and evolutionary relationships based on tumor DNA sequencing data. - Ali F. Alsulami
Mut-Map: Comprehensive Computational Pipeline for Structural Mapping and Analysis of Cancer-Associated Mutations. - Jingkai Wang
A multi-omics study of brain tissue transcription and DNA methylation revealing the genetic pathogenesis of ADHD. - Mingjun Ji, Qing Yu, Xinzhuang Yang, Xianhong Yu, Jiaxin Wang, Chunfu Xiao, Ni A. An, Chuanhui Han, Chuan-Yun Li
Long-range alternative splicing contributes to neoantigen specificity in glioblastoma. - Lin Yuan
scMGATGRN: a multiview graph attention network-based method for inferring gene regulatory networks from single-cell transcriptomic data. - Muhammad A Nawaz
Bioinformatics in Russia: history and present-day landscape. - Xinwan Su, Chengyu Shi, Fangzhou Liu, Manman Tan, Ying Wang, Linyu Zhu, Yu Chen, Meng Yu, Xinyi Wang, Jian Liu, Yang Liu, Weiqiang Lin, Zhaoyuan Fang, Qiang Sun, Tianhua Zhou, Aifu Lin
HMPA: a pioneering framework for the noncanonical peptidome from discovery to functional insights. - Yang Guo, Zhiqiang Xiao:
Constructing the dynamic transcriptional regulatory networks to identify phenotype-specific transcription regulators. - Jiabei Cheng, Xiaoyong Pan, Yi Fang, Kaiyuan Yang, Yiming Xue, Qingran Yan, Ye Yuan:
GexMolGen: cross-modal generation of hit-like molecules via large language model encoding of gene expression signatures. - Kathleen Noller
Cell cycle expression heterogeneity predicts degree of differentiation. - Xueying Xie
Deep learning in template-free de novo biosynthetic pathway design of natural products. - Han Phan, Céline Brouard, Raphaël Mourad:
Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction. - Peihao Bai, Guanghui Li
Deep learning model for protein multi-label subcellular localization and function prediction based on multi-task collaborative training. - Sébastien De Landtsheer, Apurva Badkas
Model ensembling as a tool to form interpretable multi-omic predictors of cancer pharmacosensitivity. - Han-Ching Chan, Amrita Chattopadhyay, Tzu-Pin Lu
Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework. - Xiaoyu Li
SpaDiT: diffusion transformer for spatial gene expression prediction using scRNA-seq. - Hailin Chen
Predicting disease-associated microbes based on similarity fusion and deep learning. - Chen Su
Deciphering lineage-relevant gene regulatory networks during endoderm formation by InPheRNo-ChIP.
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