coltonlloyd's Stars
fastai/fastai
The fastai deep learning library
symengine/symengine
SymEngine is a fast symbolic manipulation library, written in C++
allegro/allRank
allRank is a framework for training learning-to-rank neural models based on PyTorch.
scverse/anndata
Annotated data.
insitro/redun
Yet another redundant workflow engine
jma127/pyltr
Python learning to rank (LTR) toolkit
opencobra/cobrapy
COBRApy is a package for constraint-based modeling of metabolic networks.
xia-lab/MetaboAnalystR
R package for MetaboAnalyst
sneumann/xcms
This is the git repository matching the Bioconductor package xcms: LC/MS and GC/MS Data Analysis
SysBioChalmers/Human-GEM
The generic genome-scale metabolic model of Homo sapiens
ElucidataInc/ElMaven
LC-MS data processing tool for large-scale metabolomics experiments.
sirius-ms/sirius
SIRIUS is a software for discovering a landscape of de-novo identification of metabolites using tandem mass spectrometry. This repository contains the code of the SIRIUS Software (GUI and CLI)
aws-samples/aws-batch-processing-job-repo
Orchestrating an Application Process with AWS Batch using AWS CloudFormation
rickhelmus/patRoon
Workflow solutions for mass-spectrometry based non-target analysis.
meowcat/MSNovelist
EMSL-Computing/CoreMS
CoreMS is a comprehensive mass spectrometry software framework
griquelme/tidyms
TidyMS: Tools for working with MS data in untargeted metabolomics
AutoFlowResearch/SmartPeak
Fast and Accurate CE-, GC- and LC-MS(/MS) Data Processing
ncats/RaMP-DB
HuanLab/BUDDY
Bottom-up MS/MS interrogation & Experiment-specific global annotation
jclachance/BOFdat
Generate biomass objective function stoichiometric coefficients for genome-scale models from experimental data
SBRG/lifelike
Turning big data into contextualized knowledge. Lifelike is a modern application platform for data extraction, analysis and visualization.
Philipbear/BUDDY_Metabolomics
Molecular formula discovery via bottom-up MS/MS interrogation
osenan/cliqueMS
Annotation of in source LC/MS data
draeger-lab/SBMLme
Encoding ME models in SBML