COSIFER: a Python package for the consensus inference of molecular interaction networks
Manica M, Bunne C, Mathis R, Cadow J, Ahsen M, Stolovitzky G, Martínez M. COSIFER: a Python package for the consensus inference of molecular interaction networks. Bioinformatics 2020, 37: 2070-2072. PMID: 33241320, PMCID: PMC8337002, DOI: 10.1093/bioinformatics/btaa942.Peer-Reviewed Original ResearchConceptsAdvent of high-throughput technologiesNetwork inferenceMolecular interaction networksHigh-throughput dataHigh-throughput technologiesState-of-the-artSupplementary dataExpression dataInteraction networkPython source codeInference servicesState-of-the-art methodologiesWeb servicesSource codeMolecular networksWeb-based platformRegulatory apparatusBioinformaticsPython packageConsensus strategyNetworkRobust networkInference methodsInferenceIndividual methodsPaccMann: a web service for interpretable anticancer compound sensitivity prediction
Cadow J, Born J, Manica M, Oskooei A, Martínez M. PaccMann: a web service for interpretable anticancer compound sensitivity prediction. Nucleic Acids Research 2020, 48: w502-w508. PMID: 32402082, PMCID: PMC7319576, DOI: 10.1093/nar/gkaa327.Peer-Reviewed Original ResearchConceptsWeb servicesAttention-based neural networkState-of-the-art methodsState-of-the-artOutputs confidence scoresCompound structure informationInteractive editorModel decision makingChemical sub-structuresAttention heatmapsNeural networkWeb-based platformModel interpretationEfficient validationConfidence scoresDrug repositioningCompound structureDrug compoundsWebSource of informationStructural informationCompoundsBiomolecular samplesDecision makingPotential compounds