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followers: 15.0 following: 12.0 repos: 16.0 gists: 1.0

Name: Jack Gisby

Type: User

Company: Queen Mary University of London

Bio: Biomedical data scientist @ Queen Mary University of London. Using and developing data science approaches to investigate disease.

Twitter: jack_gisby

Location: London

Recent projects 📂


Software packages 💻
Package Description Links
ReducedExperiment An R package that implements classes for applying and manipulating the results of dimensionality reduction GitHub
DeepMet A command line application written in Python for training and applying deep one-class models to molecular data GitHub
packFinder An R package for detecting a special type of transposon (genetic material that can move around and replicate itself) in genome sequence data GitHub Bioconductor
Academic publications 🎓
Description Links
Mining high-dimensional biological datasets to understand the response to COVID-19 Nature Comms
Predicting critical illness for COVID-19 patients Nature Comms
Modelling the temporal profiles of proteins during COVID-19 eLife
Mini projects and notebooks 📚
Description Links
Processing TfL data for bike usage with Google Cloud Platform GitHub

Stats 📊


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Jack Gisby's Projects

covid-longitudinal-multi-omics icon covid-longitudinal-multi-omics

Repository for the paper: "Multi-omics identify LRRC15 as a COVID-19 severity predictor and persistent pro-thrombotic signals in convalescence" by Gisby and Norzawani et al. doi: https://doi.org/10.1101/2022.04.29.22274267

deepmet icon deepmet

A deep one class model for the identification of endogenous metabolites.

jackgisby.github.io icon jackgisby.github.io

Site based on a Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

longitudinal_olink_proteomics icon longitudinal_olink_proteomics

Repository for the paper: "Longitudinal proteomic profiling of dialysis patients with COVID-19 reveals markers of severity and predictors of death" by Gisby et al. doi: https://doi.org/10.7554/eLife.64827

metaboblend icon metaboblend

Python package for de novo structural elucidation of small molecules in mass spectrometry-based Metabolomics

mr-nextflow icon mr-nextflow

MR for multiple exposures implemented using nextflow

packfinder icon packfinder

A package for the de novo discovery of pack-TYPE transposons

recode_rnaseq_pipeline icon recode_rnaseq_pipeline

A parallelised pipeline for the analysis of RNA sequencing data. This repository is part of Imperial College London's ReCoDE project, which aims to support teaching and learning in research computing and data science.

subset_sum icon subset_sum

Parallel implementation of subset sum in Python

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