yifengtao

genome-transformer

Predicting multiple cancer phenotypes based on somatic genomic alterations via the genomic impact transformer

CADRE

CADRE: Contextual Attention-based Drug REsponse

DeepSurv

DeepSurv is a deep learning approach to survival analysis.

roamresearch

Gene2vec-1

Gene2Vec: Distributed Representation of Genes Based on Co-Expression

picobrew

Pieces of code for biomedical research work (in Python)

yifengtao.github.io

Yifeng Tao's homepage

996.ICU

Repo for counting stars and contributing. Press F to pay respect to glorious developers.

BERT-multi-gpu

multi gpu training in one machine for BERT

bilstm_crf

chatbot_Q-A_NLP

CITRUS-1

coding-interview-university

A complete computer science study plan to become a software engineer.

DeepLearningSurvival

PyTorch implementation of Deep Survival Models.

DPPI

A convolutional neural network to predict PPI interactions

drsa

Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling.

jnci_2018

Recurrent gains in RET and HER2 signaling represent clinically actionable targets in breast cancer brain metastases

LearnToPayAttention

PyTorch implementation of ICLR 2018 paper Learn To Pay Attention (and some modification)

leetcode-share

This repository shares my leetcode problems solving experience.

LinSeed

Linseed (LINear Subspace identification for gene Expresion Deconvolution) is a package that provides tools and interface to explore gene expression datasets in linear space and perform complete gene expression deconvolution.

protein-sequence-embedding-iclr2019

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

SCS_deconvolution

code implementing methods for pooling bulk and single cell data for copy number deconvolution

Seq2Seq-PyTorch

Sequence to Sequence Models with PyTorch

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

structuredprediction.github.io

Survival-Analysis-using-Deep-Learning

This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

ticker.sh

Real-time stock tickers from the command-line.

transfer

Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks

Weaver

Allele-Specific Quantification of Structural Variations in Cancer Genomes

WebRobot

Scripts to realize ligand searching task automatically in the course: Introduction to Computational Structural Biology.