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Tero Aittokallio
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2020 – today
- 2024
- [j58]Aleksandr Ianevski
, Aleksandr Kushnir, Kristen Nader
RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies. Briefings Bioinform. 25(4) (2024) - 2023
- [j57]Potdar Swapnil
Breeze 2.0: an interactive web-tool for visual analysis and comparison of drug response data. Nucleic Acids Res. 51(W1): 57-61 (2023) - [j56]Anni S. Halkola, Kaisa Joki
OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer. PLoS Comput. Biol. 19(3) (2023) - 2022
- [j55]Vandana Ravindran
Discovery of host-directed modulators of virus infection by probing the SARS-CoV-2-host protein-protein interaction network. Briefings Bioinform. 23(6) (2022) - [j54]Petr Smirnov, Ian Smith
Evaluation of statistical approaches for association testing in noisy drug screening data. BMC Bioinform. 23(1): 188 (2022) - [j53]Aleksandr Ianevski
SynergyFinder 3.0: an interactive analysis and consensus interpretation of multi-drug synergies across multiple samples. Nucleic Acids Res. 50(W1): 739-743 (2022) - 2021
- [j52]Liye He
Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer. Briefings Bioinform. 22(6) (2021) - [j51]Tianduanyi Wang, Sándor Szedmák
Modeling drug combination effects via latent tensor reconstruction. Bioinform. 37(Supplement): 93-101 (2021) - [j50]Chen He
Characterizing the Quality of Insight by Interactions: A Case Study. IEEE Trans. Vis. Comput. Graph. 27(8): 3410-3424 (2021) - 2020
- [j49]ZiaurRehman Tanoli
Interactive visual analysis of drug-target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing. Briefings Bioinform. 21(1): 211-220 (2020) - [j48]Aleksandr Ianevski, Liye He, Tero Aittokallio, Jing Tang
SynergyFinder: a web application for analyzing drug combination dose-response matrix data. Bioinform. 36(8): 2645 (2020) - [j47]Potdar Swapnil
Breeze: an integrated quality control and data analysis application for high-throughput drug screening. Bioinform. 36(11): 3602-3604 (2020) - [j46]Mika Murtojärvi, Anni S. Halkola, Antti Airola
Cost-effective survival prediction for patients with advanced prostate cancer using clinical trial and real-world hospital registry datasets. Int. J. Medical Informatics 133 (2020) - [j45]Aleksandr Ianevski
SynergyFinder 2.0: visual analytics of multi-drug combination synergies. Nucleic Acids Res. 48(Webserver-Issue): W488-W493 (2020) - [j44]Aleksandr Ianevski
SynToxProfiler: An interactive analysis of drug combination synergy, toxicity and efficacy. PLoS Comput. Biol. 16(2) (2020) - [j43]Otto Pulkkinen
Multiobjective optimization identifies cancer-selective combination therapies. PLoS Comput. Biol. 16(12) (2020) - [i3]Chen He, Luana Micallef, Liye He, Gopal Peddinti, Tero Aittokallio, Giulio Jacucci:
Characterizing the Quality of Insight by Interactions: A Case Study. CoRR abs/2010.05723 (2020)
2010 – 2019
- 2019
- [j42]Aleksandr Ianevski
Prediction of drug combination effects with a minimal set of experiments. Nat. Mach. Intell. 1(12): 568-577 (2019) - 2018
- [j41]ZiaurRehman Tanoli
Drug Target Commons 2.0: a community platform for systematic analysis of drug-target interaction profiles. Database J. Biol. Databases Curation 2018: bay083 (2018) - [j40]Mehreen Ali
Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach. Bioinform. 34(8): 1353-1362 (2018) - [j39]Anna Cichonska
Learning with multiple pairwise kernels for drug bioactivity prediction. Bioinform. 34(13): i509-i518 (2018) - [j38]Teemu D. Laajala
ePCR: an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts. Bioinform. 34(22): 3957-3959 (2018) - 2017
- [j37]Muhammad Ammad-ud-din, Suleiman A. Khan, Krister Wennerberg
Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression. Bioinform. 33(14): i359-i368 (2017) - [j36]Aleksandr Ianevski
SynergyFinder: a web application for analyzing drug combination dose-response matrix data. Bioinform. 33(15): 2413-2415 (2017) - [j35]Chen He
MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection. BMC Bioinform. 18(S-10): 393:1-393:12 (2017) - [j34]Balaguru Ravikumar
C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms. Nucleic Acids Res. 45(Webserver-Issue): W495-W500 (2017) - [j33]Anna Cichonska
Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. PLoS Comput. Biol. 13(8) (2017) - 2016
- [j32]Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani
Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization. Bioinform. 32(17): 455-463 (2016) - [i2]Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani, Astrid Murumägi, Olli-P. Kallioniemi, Tero Aittokallio, Samuel Kaski:
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization. CoRR abs/1606.03623 (2016) - 2015
- [j31]Tapio Pahikkala
Toward more realistic drug-target interaction predictions. Briefings Bioinform. 16(2): 325-337 (2015) - [j30]Liye He
TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples. Bioinform. 31(11): 1866-1868 (2015) - [j29]John-Patrick Mpindi, Potdar Swapnil
Impact of normalization methods on high-throughput screening data with high hit rates and drug testing with dose-response data. Bioinform. 31(23): 3815-3821 (2015) - 2014
- [j28]Jing Tang
Making Sense of Large-Scale Kinase Inhibitor Bioactivity Data Sets: A Comparative and Integrative Analysis. J. Chem. Inf. Model. 54(3): 735-743 (2014) - [c5]Tapio Pahikkala
A Two-Step Learning Approach for Solving Full and Almost Full Cold Start Problems in Dyadic Prediction. ECML/PKDD (2) 2014: 517-532 - [i1]Tapio Pahikkala, Michiel Stock, Antti Airola, Tero Aittokallio, Bernard De Baets, Willem Waegeman:
A two-step learning approach for solving full and almost full cold start problems in dyadic prediction. CoRR abs/1405.4423 (2014) - 2013
- [j27]Sebastian Okser, Tapio Pahikkala
Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives. BioData Min. 6: 5 (2013) - [j26]Jing Tang
Target Inhibition Networks: Predicting Selective Combinations of Druggable Targets to Block Cancer Survival Pathways. PLoS Comput. Biol. 9(9) (2013) - 2012
- [j25]Tapio Pahikkala
Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations. Algorithms Mol. Biol. 7: 11 (2012) - [j24]Johannes Tuikkala, Heidi Vähämaa, Pekka Salmela, Olli Nevalainen, Tero Aittokallio
A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization. BioData Min. 5: 2 (2012) - [j23]Marja A. Heiskanen
Mining high-throughput screens for cancer drug targets - lessons from yeast chemical-genomic profiling and synthetic lethality. WIREs Data Mining Knowl. Discov. 2(3): 263-272 (2012) - [c4]Sebastian Okser, Antti Airola
Parallel Feature Selection for Regularized Least-Squares. PARA 2012: 280-294 - 2011
- [j22]Rolf Lindén, Ville-Pekka Eronen, Tero Aittokallio
Quantitative maps of genetic interactions in yeast - Comparative evaluation and integrative analysis. BMC Syst. Biol. 5: 45 (2011) - [j21]Leo Lahti
Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays. IEEE ACM Trans. Comput. Biol. Bioinform. 8(1): 217-225 (2011) - [c3]Sebastian Okser, Tapio Pahikkala
Fast and parallelized greedy forward selection of genetic variants in Genome-wide association studies. GENSiPS 2011: 214-217 - 2010
- [j20]Tero Aittokallio
Dealing with missing values in large-scale studies: microarray data imputation and beyond. Briefings Bioinform. 11(2): 253-264 (2010)
2000 – 2009
- 2009
- [j19]Laura Elo
Optimized detection of differential expression in global profiling experiments: case studies in clinical transcriptomic and quantitative proteomic datasets. Briefings Bioinform. 10(5): 547-555 (2009) - [j18]Mathieu Clément-Ziza
Genoscape: a Cytoscape plug-in to automate the retrieval and integration of gene expression data and molecular networks. Bioinform. 25(19): 2617-2618 (2009) - 2008
- [j17]Arho Virkki, Olli Polo, Tarja Saaresranta, Anne Laapotti-Salo, Mats Gyllenberg
Overnight features of transcutaneous carbon dioxide measurement as predictors of metabolic status. Artif. Intell. Medicine 42(1): 55-65 (2008) - [j16]Virpi Ahola, Tero Aittokallio
Model-based prediction of sequence alignment quality. Bioinform. 24(19): 2165-2171 (2008) - [j15]Johannes Tuikkala, Laura Elo
Missing value imputation improves clustering and interpretation of gene expression microarray data. BMC Bioinform. 9 (2008) - [j14]Laura Elo
Reproducibility-Optimized Test Statistic for Ranking Genes in Microarray Studies. IEEE ACM Trans. Comput. Biol. Bioinform. 5(3): 423-431 (2008) - 2007
- [j13]Olivier Garcia, Cosmin Saveanu
GOlorize: a Cytoscape plug-in for network visualization with Gene Ontology-based layout and coloring. Bioinform. 23(3): 394-396 (2007) - [j12]Laura Elo
Systematic construction of gene coexpression networks with applications to human T helper cell differentiation process. Bioinform. 23(16): 2096-2103 (2007) - [j11]Tero Aittokallio
Inspiratory flow shape clustering: An automated method to monitor upper airway performance during sleep. Comput. Methods Programs Biomed. 85(1): 8-18 (2007) - 2006
- [j10]Tero Aittokallio
Graph-based methods for analysing networks in cell biology. Briefings Bioinform. 7(3): 243-255 (2006) - [j9]Jussi Salmi
Quality classification of tandem mass spectrometry data. Bioinform. 22(4): 400-406 (2006) - [j8]Johannes Tuikkala, Laura Elo
Improving missing value estimation in microarray data with gene ontology. Bioinform. 22(5): 566-572 (2006) - [j7]Virpi Ahola, Tero Aittokallio
A statistical score for assessing the quality of multiple sequence alignments. BMC Bioinform. 7: 484 (2006) - [j6]Laura Elo
Inference of Gene Coexpression Networks by Integrative Analysis across Microarray Experiments. J. Integr. Bioinform. 3(2) (2006) - 2005
- [c2]Marius C. Codrea, Tero Aittokallio, Mika Keränen, Esa Tyystjärvi, Olli Nevalainen:
On the Robustness of Fluorescence Fingerprinting of Plants. Artificial Intelligence and Applications 2005: 400-405 - 2003
- [j5]Virpi Ahola, Tero Aittokallio
Efficient estimation of emission probabilities in profile hidden Markov models. Bioinform. 19(18): 2359-2368 (2003) - [j4]Tero Aittokallio, Markus Kurki, Olli Nevalainen, Tuomas Nikula, Anne West, Riitta Lahesmaa:
Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments. J. Bioinform. Comput. Biol. 1(3): 541-586 (2003) - [j3]Marius C. Codrea, Tero Aittokallio
Feature learning with a genetic algorithm for fluorescence fingerprinting of plant species. Pattern Recognit. Lett. 24(15): 2663-2673 (2003) - [c1]Marius C. Codrea, Tero Aittokallio
Genetic Feature Learning Algorithm for Fluorescence Fingerprinting of Plants. Artificial Evolution 2003: 371-383 - 2000
- [j2]Tero Aittokallio
Detection of high-frequency respiratory movements during sleep. Comput. Methods Programs Biomed. 61(3): 171-185 (2000)
1990 – 1999
- 1999
- [j1]Tero Aittokallio
Classification of Nasal Inspiratory Flow Shapes by Attributed Finite Automata. Comput. Biomed. Res. 32(1): 34-55 (1999)
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last updated on 2024-10-07 21:24 CEST by the dblp team
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