Life Sciences

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  Deep Reinforcement Learning for De Novo Drug Design

  • Published on: July, 2018
  • Olexandr Isayev, Mariya Popova, Alexander Tropsha
  • Code Available

  This model is an implementation of a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcemen ...

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  CT Based COVID-19 triage Deep multitask learning improves joint identification and severity quantification

  • Published on: March, 2021
  • MikhailGoncharov, MaximPisov
  • Code Available

  Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem ...

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  A Bayesian time-to-event pharmacokinetic model for phase I dose-escalation trials with multiple schedules

  • Published on: July, 2019
  • S Weber, BK Günhan, and T Friede
  • Code Available

  TITE-PK (a time-to-event pharmacokinetic model) is a method for designing and analyzing phase I dose-escalation trials with multiple schedules, eg a d ...

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  Xome-Blender-A Novel Cancer Genome Simulator

  • Published on: April, 2018
  • A. Magi, R. Semeraro, Valerio Orlandini
  • Code Available

  Xome-Blender is a collection of python and R scripts based on SAMtools functions that allows to generate synthetic cancer genomes with user defined fe ...

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  Attend and Predict-Understanding Gene Regulation by Selective Attention on Chromatin

  • Published on: May, 2018
  • Jack Lanchantin, Ritambhara Singh, Arshdeep Sekhon, Yanjun Qi
  • Code Available

  AttentiveChrome is an attention-based deep learning model that uses histone modification signals covering the gene’s neighboring DNA region of Transcr ...

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  GAMENet - Graph Augmented Memory Networks for Recommending Medication Combination

  • Published on: November, 2018
  • Hongyan Li, Tengfei Ma, Jimeng Sun, Cao Xiao, Junyuan Shang
  • Code Available

  When it comes to recommend medication combination for patients with complex health conditions, existing deep learning approaches either do not customi ...

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  Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

  • Published on: September, 2021
  • Logan Ward, Chi Chen, Shyue Ping Ong
  • Code Available

  This repository represents the efforts of the Materials Virtual Lab in developing graph networks for machine learning in materials science. It is a wo ...

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  Predicting mRNA Abundance Directly from Genomic Sequence using Deep Convolutional Neural Networks

  • Published on: June, 2020
  • Jay Shendure, Vikram Agarwal
  • Code Available

  The model shows that mRNA abundance can be predicted from promoter sequence alone using deep neural networks. The residuals of these predictions make ...

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  NanoSim-Nanopore Sequence read Simulator

  • Published on: April, 2017
  • Inanç Birol , René L Warren, Justin Chu, Chen Yang
  • Code Available

  NanoSim is a nanopore sequence read simulator based on statistical characterization. It is a fast and scalable read simulator that captures the techno ...

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  Adverse Drug Reaction(ADR)-Target Association Prediction

  • Published on: July, 2020
  • Bumjun Kim, Seda Arat, Robert Ietswaart, William DuMouchel, Saman Farahmand, Amanda X. Chen
  • Code Available

  Adverse reactions of marketed and approved drugs cause a significant amount of morbidity and mortality. To associate these drugs with human adverse dr ...