AI and Machine Learning


  • ACRE -  absolute concentration robustness exploration in module-based networks

  • DEEP - a general computational framework for predicting enhancers (NAR)

  • DRAF -  a transcription factor (TF) binding site (TFBS) prediction tool

  • DragonWFS - a parallel GA wrapper feature selection tool for optimizing the performance of different classification methods

  • Dragon TF-TcoF Classifier - predicts and assigns a functional class of a protein that binds a transcription factor (TF)

  • Drug-Target Interaction tool (DDR) -  predicts drug target interactions using multiple similarities

  • ElVira - an ontology modularization tool

  • FSFE - identifying enhancer signatures based on state-of-the-art computational techniques

  • Gracob - a graph-based biclustering method that is designed to find maximal constant-column biclusters in any given two-dimensional data matrix, particularly growth phenotype data in which each row represents a gene deletion strain and each column represents a stress condition

  • NMR slice picking and resonance assignment - This toos has two components, one for NMR slice picking and the other one for resonance assignment based on picked sliced

  • OmniGA - a framework for the optimization of omnivariate decision trees (ODTs) based on a parallel genetic algorithm (GA)

  • PEDAL - discriminative identification of transcriptional responses of promoters and enhancers after stimulus (NAR)

  • PEDI - parameter Estimation by Decomposition and Integration

  • Walking RDF and OWL - feature learning on knowledge graphs and ontologies