Life Sciences

• 

  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 ...

• 

  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 ...

• 

  BABEL enables Cross-modality Translation between Multiomic Profiles at Single-cell Resolution

  • Published on: November, 2020
  • Kevin E. Wu, Kathryn E. Yost, Howard Y. Chang and James Zoua

  BABEL is a deep learning model written in Python designed to translate between mutliple single cell modalities. It is designed to translate between sc ...

• 

  BPNet-Base-Resolution Models of Transcription Factor Binding Reveal Soft Motif Syntax

  • Published on: February, 2021
  •  Amr Alexandari,  Anshul Kundaje,  Julien Gagneur,  Khyati Dalal, Žiga Avsec,  Avanti Shrikumar,  Charles McAn...
  • Code Available

  A crucial part of the cis-regulatory code is the arrangement of transcription factor binding motifs. But, identifying the critical bases that alter th ...

• 

  Integrating Spatial Gene Expression and Breast Tumour Morphology via Deep Learning

  • Published on: June, 2020
  • Åke Borg, Joakim Lundeberg, Linnea Stenbeck, Bryan He, Abubakar Abid, Jonas Maaskola, James Zou, Alma Andersso...
  • Code Available

  Machine Learning is becoming a powerful approach for integrative analysis of whole slide histology images. More recently, convolutional neural network ...

• 

  Effective Gene Expression Prediction from Sequence by Integrating Long-range Interactions

  • Published on: April, 2021
  • Daniel Visentin, Žiga Avsec, Kyle R. Taylor, John Jumper, Pushmeet Kohli, Yannis Assael, View ORCID ProfileDav...
  • Code Available

  Predicting gene expression purely from DNA sequence has been a long-standing problem in regulatory genomics. Enformer is a novel transformer architect ...

• 

  Kipoi-Accelerating The Community Exchange and Reuse of Predictive Models for Genomics

  • Published on: July, 2018
  • Žiga Avsec, Anshul Kundaje, Jun Cheng, Abhimanyu Banerjee, Julien Gagneur, Avanti Shrikumar, Lara Urban, Roman...
  • Code Available

  Advanced machine learning models applied to large-scale genomics datasets hold the promise to be major drivers for genome science. Once trained, such ...

• 

  OmiEmbed-A Unified Multi-task Deep Learning Framework for Multi-omics Data

  • Published on: May, 2021
  • Kai Sun and Yike Guo, Xiaoyu Zhang, Yuting Xing
  • Code Available

  OmiEmbed is a unified multitask deep learning framework that captures biomedical information from high-dimensional omics data with the deep embedding ...

• 

  XOmiVAE-An Interpretable Deep Learning Model for Cancer Classification Using High-Dimensional Omics Data

  • Published on: May, 2021
  • Kai Sun, Yike Guo, Xiaoyu Zhang, Eloise Withnell
  • Code Available

  XOmiVAE is an interpretable deep learning model for cancer classification using high-dimensional omics data. It provides contribution of each input mo ...

• 

  A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes

  • Published on: July, 2020
  • Ulisses Braga-Neto, Caio Davi
  • Code Available

  For most diseases, building large databases of labeled genetic data is an expensive and time-demanding task. genetic Generative Adversarial Networks ...