Stars
Standardised Metrics and Methods for Synthetic Tabular Data Evaluation
A curated list of resources for using LLMs to develop more competitive grant applications.
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
The Distributed Computing library for python implemented using PyCOMPSs programming model for HPC.
Python package for machine learning for healthcare using a OMOP common data model
Snakemake pipeline that works with the scIB package to benchmark data integration methods.
Fit Gamma-Poisson Generalized Linear Models Reliably
A python-based package and software to predict metabolite mediated cell-cell communications by single-cell RNA-seq data
[ML4H 2022] This is the code for our paper `Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions on EHR'.
Interactive tutorials for using scikit-bio in biological research
Python library for implementing Responsible AI mitigations.
gReLU is a python library to train, interpret, and apply deep learning models to DNA sequences.
(DRExM³L) Drug REpurposing using eXplainable Machine Learning and Mechanistic Models of signal transduction
Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI
Official implementation for HyenaDNA, a long-range genomic foundation model built with Hyena
Additional code and analysis from the single-cell integration benchmarking project
A massively parallel, high-level programming language
There can be more than Notion and Miro. AFFiNE(pronounced [ə‘fain]) is a next-gen knowledge base that brings planning, sorting and creating all together. Privacy first, open-source, customizable an…
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
TRAjectory-based Differential Expression analysis for SEQuencing data
A complete guide for analyzing bulk RNA-seq data. Go from raw FASTQ files to mapping reads using STAR and differential gene expression analysis using DESeq2, using example data from Guo et al. 2019.
An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
Source code for the R package, "dbparser" (i.e. DrugBank Parser)
VIP cheatsheets for Stanford's CS 229 Machine Learning