Seana4rd

Seana4rd's Stars

• MLNLP-World/Paper-Writing-Tips

  MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

  3.7k474

• EasyChart/Beautiful-Visualization-with-R

  《R语言数据可视化之美》配套代码

  Language:PostScript782552

• idekerlab/nest_vnn

  NeST-VNN repo

  Language:Python104

• JieZheng-ShanghaiTech/MiT4SL

  MiT4SL is the first machine learning model for cross cell line prediction of synthetic lethal (SL) gene pairs. It uses a novel method of triplet representation learning to encode cell line information by integrating multi-omics data of gene expression, PPI network and protein sequences, etc.

  Language:Python3

• OmicsML/awesome-deep-learning-single-cell-papers

  71092

• korawat-tanwisuth/Proto_DA

  Language:Python435

• joanagoncalveslab/ELISL

  ELISL: Early-Late Synthetic Lethality Prediction in Cancer by Tepeli YI, Seale C, Gonçalves JP (bioRxiv 2022, Bioinformatics 2023)

  Language:Python3

• peizhenbai/DrugBAN

  Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

  Language:Python11115

• SejeongPark8354/MforDrugDev

  21

• cyrilmory/OneStepSpectralCT

  Matlab code for spectral CT one-step inversion. Implementation of five different methods

  Language:TeX119

• JieZheng-ShanghaiTech/LukePi

  Language:Python2

• cran/GOSim

  Computation of functional similarities between GO terms and gene

  Language:TeX21

• JieZheng-ShanghaiTech/SL_benchmark

  Benchmarking study of machine learning methods for prediction of synthetic lethality

  Language:Python122

• KevinMusgrave/pytorch-metric-learning

  The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

  Language:Python6.1k656

• HanwenXuTHU/Pisces

  Language:Jupyter Notebook7

• RElbers/info-nce-pytorch

  PyTorch implementation of the InfoNCE loss for self-supervised learning.

  Language:Python50841

• JieZheng-ShanghaiTech/SynLethDB

  SynLethDB is a comprehensive database (and knowledgebase) for synthetic lethality, a promising strategy of cancer therapeutics and drug discovery

  32

• wey-gu/nebula-dgl

  NebulaGraph DGL(Deep Graph Library) Integration Package. (WIP)

  Language:Python373

• d2l-ai/d2l-en

  Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

  Language:Python24.4k4.4k

• safe-graph/DGFraud

  A Deep Graph-based Toolbox for Fraud Detection

  Language:Python700159

• linjc16/Pisces

  [RECOMB 2023] Official implementation of "Pisces: A combo-wise contrastive learning approach to synergistic drug combination prediction".

  Language:Python14

• iwuqing/Polyner

  [NeurIPS 2023] Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction

  Language:MATLAB325

• sheldonresearch/ProG

  A Unified Python Library for Graph Prompting

  Language:Python53465

• d2l-ai/d2l-zh

  《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

  Language:Python64.7k11.1k

• MingchaoZhu/DeepLearning

  Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

  Language:Python6.6k1.3k

• HKUDS/LightGCL

  [ICLR'2023] "LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation"

  Language:Python18116

• r-three/t-few

  Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

  Language:Python43761

• LPioL/MultiVERSE

  Language:Python1810

• JieZheng-ShanghaiTech/PiLSL

  PiLSL is a pairwise interaction learning-based graph neural network (GNN) model for prediction of synthetic lethality (SL) as anti-cancer drug targets. It learns the representation of pairwise interaction between two genes from a knowledge graph (KG).

  Language:Python101

• THUDM/GraphMAE2

  GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23

  Language:Python14515