BMC Bioinformatics, Volume 22 - Supplements

Volume 22-S, Number 1, December 2021

Recent Progresses with BioNLP Open Shared Tasks - Part 2

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  Lenz Furrer, Joseph Cornelius, Fabio Rinaldi:
  Parallel sequence tagging for concept recognition. 623

Volume 22-S, Number 2, April 2021

15th and 16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2018-19)

• 
  Changhee Han, Leonardo Rundo, Kohei Murao, Tomoyuki Noguchi, Yuki Shimahara, Zoltán Ádám Milacski, Saori Koshino, Evis Sala, Hideki Nakayama, Shin'ichi Satoh:
  MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction. 31
• 
  Daniele D'Agostino, Pietro Liò, Marco Aldinucci, Ivan Merelli:
  Advantages of using graph databases to explore chromatin conformation capture experiments. 43
• 
  Caro Fuchs, Marco S. Nobile, Guillaume Zamora, Aurélie Degeneffe, Pieter Leonard Kubben, Uzay Kaymak:
  Tremor assessment using smartphone sensor data and fuzzy reasoning. 57
• 
  Albane Lysiak, Guillaume Fertin, Géraldine Jean, Dominique Tessier:
  Evaluation of open search methods based on theoretical mass spectra comparison. 65
• 
  Marco S. Nobile, Vasco Coelho, Dario Pescini, Chiara Damiani:
  Accelerated global sensitivity analysis of genome-wide constraint-based metabolic models. 78
• 
  Paolo Cazzaniga, Maria Raposo, Daniela Besozzi, Ivan Merelli, Antonino Staiano, Angelo Ciaramella, Riccardo Rizzo, Luca Manzoni:
  Selected papers from the 15th and 16th international conference on Computational Intelligence Methods for Bioinformatics and Biostatistics. 90
• 
  Mahdi Shafiee Kamalabad, Marco Grzegorczyk:
  A new Bayesian piecewise linear regression model for dynamic network reconstruction. 196

Volume 22-S, Number 3, May 2021

Proceedings of the 2019 International Conference on Intelligent Computing (ICIC 2019): bioinformatics

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  Sijia Zhang, Lihua Wang, Le Zhao, Menglu Li, Mengya Liu, Ke Li, Yannan Bin, Junfeng Xia:
  An improved DNA-binding hot spot residues prediction method by exploring interfacial neighbor properties. 253
• 
  Jin-Xing Liu, Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Feng Li:
  DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization. 241
• 
  Jun Meng, Qiang Kang, Zheng Chang, Yushi Luan:
  PlncRNA-HDeep: plant long noncoding RNA prediction using hybrid deep learning based on two encoding styles. 242
• 
  Junyi Li, Huinian Li, Xiao Ye, Li Zhang, Qingzhe Xu, Yuan Ping, Xiaozhu Jing, Wei Jiang, Qing Liao, Bo Liu, Yadong Wang:
  IIMLP: integrated information-entropy-based method for LncRNA prediction. 243
• 
  Hai-Cheng Yi, Zhu-Hong You, Lei Wang, Xiao-Rui Su, Xi Zhou, Tong-Hai Jiang:
  In silico drug repositioning using deep learning and comprehensive similarity measures. 293
• 
  Enze Zhang, Boheng Zhang, Shaohan Hu, Fa Zhang, Zhiyong Liu, Xiaohua Wan:
  Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks. 327
• 
  Shunfang Wang, Lin Deng, Xinnan Xia, Zicheng Cao, Yu Fei:
  Predicting antifreeze proteins with weighted generalized dipeptide composition and multi-regression feature selection ensemble. 340
• 
  Haoran Zhou, Jael Sanyanda Wekesa, Yushi Luan, Jun Meng:
  PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions. 415
• 
  Bin Yang, Wenzheng Bao, Wei Zhang, Haifeng Wang, Chuandong Song, Yuehui Chen, Xiuying Jiang:
  Reverse engineering gene regulatory network based on complex-valued ordinary differential equation model. 448
• 
  Maël Conan, Nathalie Théret, Sophie Langouet, Anne Siegel:
  Constructing xenobiotic maps of metabolism to predict enzymes catalyzing metabolites capable of binding to DNA. 450
• 
  Shuang Ma, Dan Dang, Wenxue Wang, Yuechao Wang, Lianqing Liu:
  Concentration optimization of combinatorial drugs using Markov chain-based models. 451
• 
  Yun-Yun Tang, Pi-Jing Wei, Jian-ping Zhao, Junfeng Xia, Rui-Fen Cao, Chun-Hou Zheng:
  Identification of driver genes based on gene mutational effects and network centrality. 457
• 
  Yuqing Qian, Limin Jiang, Yijie Ding, Jijun Tang, Fei Guo:
  A sequence-based multiple kernel model for identifying DNA-binding proteins. 291
• 
  Weizhong Lu, Yan Cao, Hongjie Wu, Yijie Ding, Zhengwei Song, Yu Zhang, Qiming Fu, Haiou Li:
  Research on RNA secondary structure predicting via bidirectional recurrent neural network. 431
• 
  Toshitaka Tanebe, Takashi Ishida:
  End-to-end learning for compound activity prediction based on binding pocket information. 529
• 
  Zhongting Jiang, Dong Wang, Yuehui Chen:
  Automatic classification of nerve discharge rhythms based on sparse auto-encoder and time series feature. 619

Volume 22-S, Number 4, October 2021

Accelerating Bioinformatics Research with ICIBM 2020 (part 2)

• 
  Yusong Liu, Xiufen Ye, Christina Y. Yu, Wei Shao, Jie Hou, Weixing Feng, Jie Zhang, Kun Huang:
  TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery. 111
• 
  Zexian Zeng, Chengsheng Mao, Andy H. Vo, Xiaoyu Li, Janna Ore Nugent, Seema A. Khan, Susan E. Clare, Yuan Luo:
  Deep learning for cancer type classification and driver gene identification. 491

Volume 22-S, Number 5, November 2021

Proceedings of the International Conference on Biomedical Engineering Innovation (ICBEI) 2019-2020

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  Ping-Nan Chen, Chia-Chiang Lee, Chang-Min Liang, Shu-I Pao, Ke-Hao Huang, Ke-Feng Lin:
  General deep learning model for detecting diabetic retinopathy. 84
• 
  Wen-Hsien Ho, Tian-Hsiang Huang, Po-Yuan Yang, Jyh-Horng Chou, Jin-Yi Qu, Po-Chih Chang, Fu-I Chou, Jinn-Tsong Tsai:
  Robust optimization of convolutional neural networks with a uniform experiment design method: a case of phonocardiogram testing in patients with heart diseases. 92
• 
  Cai Wu, Maxwell Hwang, Tian-Hsiang Huang, Yenming J. Chen, Yiu-Jen Chang, Tsung-Han Ho, Jian Huang, Kao-Shing Hwang, Wen-Hsien Ho:
  Application of artificial intelligence ensemble learning model in early prediction of atrial fibrillation. 93
• 
  Da Wang, Maxwell Hwang, Wei-Cheng Jiang, Kefeng Ding, Hsiao Chien Chang, Kao-Shing Hwang:
  A deep learning method for counting white blood cells in bone marrow images. 94
• 
  Yao-Mei Chen, Wei-Tai Huang, Wen-Hsien Ho, Jinn-Tsong Tsai:
  Classification of age-related macular degeneration using convolutional-neural-network-based transfer learning. 99
• 
  Chien-Hung Lee, Ko Chang, Yao-Mei Chen, Jinn-Tsong Tsai, Yenming J. Chen, Wen-Hsien Ho:
  Epidemic prediction of dengue fever based on vector compartment model and Markov chain Monte Carlo method. 118
• 
  Yao-Mei Chen, Yenming J. Chen, Wen-Hsien Ho, Jinn-Tsong Tsai:
  Classifying chest CT images as COVID-19 positive/negative using a convolutional neural network ensemble model and uniform experimental design method. 147
• 
  Wen-Hsien Ho, Tian-Hsiang Huang, Po-Yuan Yang, Jyh-Horng Chou, Hong-Siang Huang, Li-Chung Chi, Fu-I Chou, Jinn-Tsong Tsai:
  Artificial intelligence classification model for macular degeneration images: a robust optimization framework for residual neural networks. 148
• 
  Shinfeng D. Lin, Luming Chen, Wensheng Chen:
  Thermal face recognition under different conditions. 313
• 
  Hui Yu, Jinqiu Li, Lixin Zhang, Yuzhen Cao, Xuyao Yu, Jinglai Sun:
  Design of lung nodules segmentation and recognition algorithm based on deep learning. 314
• 
  Yao-Mei Chen, Fu-I Chou, Wen-Hsien Ho, Jinn-Tsong Tsai:
  Classifying microscopic images as acute lymphoblastic leukemia by Resnet ensemble model and Taguchi method. 615
• 
  Ermal Elbasani, Soualihou Ngnamsie Njimbouom, Tae-Jin Oh, Eung-Hee Kim, Hyun Lee, Jeong-Dong Kim:
  GCRNN: graph convolutional recurrent neural network for compound-protein interaction prediction. 616
• 
  Hao-Hsiang Ku, Pinpin Lin, Min-Pei Ling:
  Assessment of potential human health risks in aquatic products based on the heavy metal hazard decision tree. 620
• 
  Zhen-Hao Guo, Zhan-Heng Chen, Zhu-Hong You, Yan-Bin Wang, Hai-Cheng Yi, Mei-Neng Wang:
  A learning-based method to predict LncRNA-disease associations by combining CNN and ELM. 622
• 
  Chih-Yuan Wei, Ping-Nan Chen, Shih-Sung Lin, Tsai-Wang Huang, Ling-Chun Sun, Chun-Wei Tseng, Ke-Feng Lin:
  Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness. 628
• 
  Yuhu Wang, Yuzhen Cao, Jinqiu Li, Hongtao Wu, Shuo Wang, Xinming Dong, Hui Yu:
  A lightweight hierarchical convolution network for brain tumor segmentation. 636
• 
  Wen-Hsien Ho, Tian-Hsiang Huang, Yenming J. Chen, Lang-Yin Zeng, Fen-Fen Liao, Yeong-Cheng Liou:
  Prediction of vancomycin initial dosage using artificial intelligence models applying ensemble strategy. 637
• 
  Chien-Cheng Lee, Hong-Han Chau, Hsiao-Lun Wang, Yi-Fang Chuang, Yawgeng Chau:
  Mild cognitive impairment prediction based on multi-stream convolutional neural networks. 638

Volume 22-S, Number 6, June 2021

19th International Conference on Bioinformatics 2020 (InCoB2020)

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  Hao Jia, Sung-Joon Park, Kenta Nakai:
  A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations. 128
• 
  Guo-Sheng Han, Qi Li, Ying Li:
  Comparative analysis and prediction of nucleosome positioning using integrative feature representation and machine learning algorithms. 129
• 
  Ruiyi Li, Jihong Guan, Shuigeng Zhou:
  Boosting scRNA-seq data clustering by cluster-aware feature weighting. 130
• 
  Xinnan Dai, Fan Xu, Shike Wang, Piyushkumar A. Mundra, Jie Zheng:
  PIKE-R2P: Protein-protein interaction network-based knowledge embedding with graph neural network for single-cell RNA to protein prediction. 139
• 
  Xuan Zhang, Yuansheng Liu, Zuguo Yu, Michael Blumenstein, Gyorgy Hutvagner, Jin-Yan Li:
  Instance-based error correction for short reads of disease-associated genes. 142
• 
  Haoran Ma, Tin Wee Tan, Kenneth Ban Hon Kim:
  A multi-task CNN learning model for taxonomic assignment of human viruses. 194
• 
  Shiu Kumar, Tatsuhiko Tsunoda, Alok Sharma:
  SPECTRA: a tool for enhanced brain wave signal recognition. 195
• 
  Kuo-Ching Liang, Yasubumi Sakakibara:
  MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenome assembly. 427
• 
  Shiu Kumar, Ronesh Sharma, Tatsuhiko Tsunoda, Thirumananseri Kumarevel, Alok Sharma:
  Forecasting the spread of COVID-19 using LSTM network. 316
• 
  Yasmine Mansour, Annie Chateau, Anna-Sophie Fiston-Lavier:
  BREC: an R package/Shiny app for automatically identifying heterochromatin boundaries and estimating local recombination rates along chromosomes. 396
• 
  Xuan Zhang, Jing Li, Bang-Zhen Pan, Wen Chen, Maosheng Chen, Mingyong Tang, Zeng-Fu Xu, Changning Liu:
  Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data. 409
• 
  Weixia Xu, Yangyun Gao, Yang Wang, Jihong Guan:
  Protein-protein interaction prediction based on ordinal regression and recurrent convolutional neural networks. 485
• 
  Ling Wan, Justin Song, Virginia He, Jennifer Roman, Grace Whah, Suyuan Peng, Luxia Zhang, Yongqun He:
  Development of the International Classification of Diseases Ontology (ICDO) and its application for COVID-19 diagnostic data analysis. 508

Volume 22-S, Number 7, July 2021

Proceedings from the Joint NETTAB/BBCC 2019 Conference (part 2)

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  Carlo Ferravante, Domenico Memoli, Domenico A. Palumbo, Paolo Ciaramella, Antonio Di Loria, Ylenia D'Agostino, Giovanni Nassa, Francesca Rizzo, Roberta Tarallo, Alessandro Weisz, Giorgio Giurato:
  HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities): a specific and comprehensive pipeline for metagenomic shotgun sequencing data analysis. 106
• 
  Anna Marabotti, Eugenio Del Prete, Bernardina Scafuri, Angelo M. Facchiano:
  Performance of Web tools for predicting changes in protein stability caused by mutations. 345

Volume 22-S, Number 8, April 2021

Selected papers from the 3rd International Workshop on Computational Methods for the Immune System Function (CMISF 2019) - part 2

• 
  Guanglan Zhang, Lou Chitkushev, Lars Rønn Olsen, Derin B. Keskin, Vladimir Brusic:
  TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes. 40

Volume 22-S, Number 9, August 2021

Selected articles from the Biological Ontologies and Knowledge bases workshop 2019: part 2

• 
  Syed Ahmad Chan Bukhari, Shrikant Pawar, Jeff Mandell, Steven H. Kleinstein, Kei-Hoi Cheung:
  LinkedImm: a linked data graph database for integrating immunological data. 105
• 
  Wei Quan, Bo Liu, Yadong Wang:
  Fast and SNP-aware short read alignment with SALT. 172
• 
  Yan Wang, Zuheng Xia, Jingjing Deng, Xianghua Xie, Maoguo Gong, Xiaoke Ma:
  TLGP: a flexible transfer learning algorithm for gene prioritization based on heterogeneous source domain. 274
• 
  Jiajie Peng, Lu Han, Xuequn Shang:
  A novel method for predicting cell abundance based on single-cell RNA-seq data. 281
• 
  Tao Wang, Yongzhuang Liu, Junpeng Ruan, Xianjun Dong, Yadong Wang, Jiajie Peng:
  A pipeline for RNA-seq based eQTL analysis with automated quality control procedures. 403
• 
  Che-Yu Chou, Pinpin Lin, Jongwoon Kim, Shan-Shan Wang, Chia-Chi Wang, Chun-Wei Tung:
  Ensemble learning for predicting ex vivo human placental barrier permeability. 629

Volume 22-S, Number 10, December 2021

Selected articles from the 19th Asia Pacific Bioinformatics Conference (APBC 2021): bioinformatics

• 
  Eskezeia Yihunie Dessie, Jeffrey J. P. Tsai, Jan-Gowth Chang, Ka-Lok Ng:
  A novel miRNA-based classification model of risks and stages for clear cell renal cell carcinoma patients. 270
• 
  Wei-Sheng Wu, Yi-Hong Tsao, Sheng-Cian Shiue, Ting-Yu Chen, Yan Yuan Tseng, Joseph T. Tseng:
  A tool for analyzing and visualizing ribo-seq data at the isoform level. 271
• 
  Yu-Te Lin, Ko-Hong Lin, Chi-Jung Huang, An-Chi Wei:
  MitoTox: a comprehensive mitochondrial toxicity database. 369
• 
  Liang Shu, Cheng Zhou, Xinxu Yuan, Jingpu Zhang, Lei Deng:
  MSCFS: inferring circRNA functional similarity based on multiple data sources. 371
• 
  Zhenmiao Zhang, Lu Zhang:
  METAMVGL: a multi-view graph-based metagenomic contig binning algorithm by integrating assembly and paired-end graphs. 378
• 
  Xi Yang, Chengkun Wu, Goran Nenadic, Wei Wang, Kai Lu:
  Mining a stroke knowledge graph from literature. 387
• 
  Victoria Bourgeais, Farida Zehraoui, Mohamed Ben Hamdoune, Blaise Hanczar:
  Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data. 455
• 
  Zhijun Liao, Gaofeng Pan, Chao Sun, Jijun Tang:
  Predicting subcellular location of protein with evolution information and sequence-based deep learning. 515
• 
  Yongxian Fan, Wanru Wang:
  Using multi-layer perceptron to identify origins of replication in eukaryotes via informative features. 516
• 
  Eshan Bundhoo, Anisah W. Ghoorah, Yasmina Jaufeerally-Fakim:
  TAGOPSIN: collating taxa-specific gene and protein functional and structural information. 517
• 
  Massimo Maiolo, Lorenzo Gatti, Diego Frei, Tiziano Leidi, Manuel Gil, Maria Anisimova:
  ProPIP: a tool for progressive multiple sequence alignment with Poisson Indel Process. 518
• 
  Fei He, Jingyi Li, Rui Wang, Xiaowei Zhao, Ye Han:
  An Ensemble Deep Learning based Predictor for Simultaneously Identifying Protein Ubiquitylation and SUMOylation Sites. 519
• 
  Yu-Ching Wu, Chia-I Chen, Peng-Ying Chen, Chun-Hung Kuo, Yi-Hsuan Hung, Kang-Yung Peng, Vin-Cent Wu, Jyy-Jih Tsai-Wu, Chia-Lang Hsu:
  GRAde: a long-read sequencing approach to efficiently identifying the CYP11B1/CYP11B2 chimeric form in patients with glucocorticoid-remediable aldosteronism. 613
• 
  Sing-Han Huang, Yu-Shu Lo, Yong-Chun Luo, Yi-Hsuan Chuang, Jung-Yu Lee, Jinn-Moon Yang:
  CoMI: consensus mutual information for tissue-specific gene signatures. 624
• 
  Tamal K. Dey, Sayan Mandal, Soham Mukherjee:
  Gene expression data classification using topology and machine learning models. 627
• 
  Kazi Zainab, Gautam Srivastava, Vijay Mago:
  Identifying health related occupations of Twitter users through word embedding and deep neural networks. 630
• 
  Conghao Wang, Xintong Lye, Rama Kaalia, Parvin Kumar, Jagath C. Rajapakse:
  Deep learning and multi-omics approach to predict drug responses in cancer. 632
• 
  Ting-Hui Wu, Cing-Han Yang, Tun-Wen Pai, Li-Ping Ho, Jen-Leih Wu, Hsin-Yiu Chou:
  Identification of fish species through tRNA-based primer design. 633
• 
  Yao-Mei Chen, Jinn-Tsong Tsai, Wen-Hsien Ho:
  Automatic identifying and counting blood cells in smear images by using single shot detector and Taguchi method. 635

Volume 22-S, Number 10, May 2021

Selected articles from the 19th Asia Pacific Bioinformatics Conference (APBC 2021): bioinformatics

• 
  Jhen Yuan Yang, Jia-Ming Chang:
  Pattern recognition of topologically associating domains using deep learning. 634

Volume 22-S, Number 11, October 2021

Proceedings of the 14th International Workshop on Data and Text Mining in Biomedical Informatics (DTMBIO 2020)

• 
  Sung-Gwon Lee, Dokyun Na, Chungoo Park:
  Comparability of reference-based and reference-free transcriptome analysis approaches at the gene expression level. 310
• 
  Joo-Seong Oh, Sung-Gwon Lee, Chungoo Park:
  PIC-Me: paralogs and isoforms classifier based on machine-learning approaches. 311
• 
  Harshit Jain, Nishant Raj, Suyash Mishra:
  A sui generis QA approach using RoBERTa for adverse drug event identification. 330
• 
  Kwangmin Kim, Doheon Lee:
  Context-aware multi-token concept recognition of biological entities. 337
• 
  Thomas Brox Røst, Laura Slaughter, Øystein Nytrø, Ashley E. Muller, Gunn E. Vist:
  Using neural networks to support high-quality evidence mapping. 496

Volume 22-S, Number 12, January 2022

Explainable AI methods in biomedical data science

• 
  Yijuan Wang, Zhi-Ping Liu:
  Identifying biomarkers for breast cancer by gene regulatory network rewiring. 308
• 
  Zhongjun Jiang, Xiaobo Li, Lijun Guo:
  MetaCRS: unsupervised clustering of contigs with the recursive strategy of reducing metagenomic dataset's complexity. 315
• 
  Kai Sun, Xiuzhen Hu, Zhenxing Feng, Hongbin Wang, Haotian Lv, Ziyang Wang, Gaimei Zhang, Shuang Xu, Xiaoxiao You:
  Predicting Ca²⁺ and Mg²⁺ ligand binding sites by deep neural network algorithm. 324
• 
  Yanhao Huo, Geng Zhao, Luoshan Ruan, Peng Xu, Gang Fang, Fengyue Zhang, Zhenshen Bao, Xin Li:
  Detect the early-warning signals of diseases based on signaling pathway perturbations on a single sample. 367
• 
  Long Yang, Li-Ping Li, Hai-Cheng Yi:
  DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph. 621
• 
  Qi Liu:
  A truncated nuclear norm and graph-Laplacian regularized low-rank representation method for tumor clustering and gene selection. 436
• 
  Hao Fu, Hui Lv, Qiang Zhang:
  Using entropy-driven amplifier circuit response to build nonlinear model under the influence of Lévy jump. 437
• 
  Henry Han, Xiangrong Liu:
  The challenges of explainable AI in biomedical data science. 443
• 
  Qing Ye, Xiaolong Zhang, Xiaoli Lin:
  Drug-target interaction prediction via multiple classification strategies. 461
• 
  Juan Wang, Cong-Hai Lu, Xiang-Zhen Kong, Ling-Yun Dai, Shasha Yuan, Xiaofeng Zhang:
  Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data. 334

Volume 22-S, Number 13, September 2021

Selected articles from the 1st International Workshop on Conceptual Modeling for Life Sciences (CMLS 2020) - Part 1

• 
  Alberto García S., Juan Carlos Casamayor:
  On how to generalize species-specific conceptual schemes to generate a species-independent Conceptual Schema of the Genome. 353
• 
  Giuseppe Agapito, Mario Cannataro:
  Using BioPAX-Parser (BiP) to enrich lists of genes or proteins with pathway data. 376
• 
  Sara Pidò, Pietro Crovari, Franca Garzotto:
  Modelling the bioinformatics tertiary analysis research process. 452

Volume 22-S, Number 14, November 2021

Selected papers from the 4th International Workshop on Computational Methods for the Immune System Function (CMISF 2020)

• 
  Paola Stolfi, Filippo Castiglione:
  Emulating complex simulations by machine learning methods. 483
• 
  Avisa Maleki, Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Francesco Pappalardo:
  In silico design of recombinant multi-epitope vaccine against influenza A virus. 617
• 
  Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Marzio Pennisi, Francesco Pappalardo:
  Model verification tools: a computational framework for verification assessment of mechanistic agent-based models. 626
• 
  Giuseppe Sgroi, Giulia Russo, Anna Maglia, Giuseppe Catanuto, Peter Barry, Andreas Karakatsanis, Nicola Rocco, Francesco Pappalardo:
  Evaluation of word embedding models to extract and predict surgical data in breast cancer. 631

Volume 22-S, Number 15, November 2021

Proceedings from the 15th Bioinformatics and Computational Biology International Conference - BBCC2020

• 
  Marco Antonio Tangaro, Pietro Mandreoli, Matteo Chiara, Giacinto Donvito, Marica Antonacci, Antonio Parisi, Angelica Bianco, Angelo Romano, Daniela Manila Bianchi, Davide Cangelosi, Paolo Uva, Ivan Molineris, Vladimir Nosi, Raffaele A. Calogero, Luca Alessandrì, Elena Pedrini, Marina Mordenti, Emanuele Bonetti, Luca Sangiorgi, Graziano Pesole, Federico Zambelli:
  Laniakea@ReCaS: exploring the potential of customisable Galaxy on-demand instances as a cloud-based service. 544
• 
  Pietro Hiram Guzzi, Giuseppe Tradigo, Pierangelo Veltri:
  Using dual-network-analyser for communities detecting in dual networks. 614
• 
  Giacomo Baruzzo, Ilaria Patuzzi, Barbara Di Camillo:
  Beware to ignore the rare: how imputing zero-values can improve the quality of 16S rRNA gene studies results. 618
• 
  Simone Ciccolella, Luca Denti, Paola Bonizzoni, Gianluca Della Vedova, Yuri Pirola, Marco Previtali:
  MALVIRUS: an integrated application for viral variant analysis. 625

Volume 22-S, Number 16, December 2021

Selected abstracts of Bioinformatics: from Algorithms to Applications 2021 conference

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  Selected abstracts of Bioinformatics: from Algorithms to Applications 2021 Conference. 591