ML in Biology

[twang15]

Topic model (NLP)

CNN for TF binding prediction

1. 2018-Nucleic Acids Research-DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants
   • Identifying variants that disrupt TF binding and lead to human diseases remains a great challenge. To address this, we implement sequence-based deep learning models that accurately predict the TF binding intensities to given DNA sequences. In addition to accurately classifying TF-DNA binding or unbinding, our models are capable of accurately predicting real-valued TF binding intensities by leveraging large-scale TF ChIP-seq data.
   • tutorial: from ChIP seq data to deep learning model

[twang15]

Kipoi: Model zoo for genomics

Kipoi (pronounce: kípi; from the Greek κήποι: gardens) is an API and a repository of ready-to-use trained models for genomics. It currently contains 2191 different models, covering canonical predictive tasks in transcriptional and post-transcriptional gene regulation

Model Zoo

Discover open source deep learning code and pretrained models.

[twang15]

ChromHMM

Chromatin state