Biochemical biomarker analysis of mussels from 74 sites across Puget Sound from the WDFW 'Mussel Watch' program.
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Updated
Jul 10, 2024 - HTML
Biochemical biomarker analysis of mussels from 74 sites across Puget Sound from the WDFW 'Mussel Watch' program.
Project to explore the Visia clinical try data.
A Python-based compendium of GPU-optimized aging clocks.
Official implementation of the Fréchet Radiomics Distance.
A library for full-stack aging clocks design and benchmarking.
Federated implementation of a CNN to predict brain age from MRI-derived gray matter
Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data (Nature Communications, 2023)
This data-centric AI repository implements a robust deep learning method (LFBNet) for fully automated tumor segmentation in whole-body [18]F-FDG PET/CT images.
This work is an initial investigation into the predictive potential of a range of machine learning algorithms applied to baseline circulating biomarkers for the prognostic stratification of patients with advanced neuroendocrine tumours receiving 177Lu oxodotreotide therapy
Profile RNA-seq data using published TB gene signatures
Personalized biomarker tracking dashboard.
A Python package for the analysis of biopsychological data.
βHΞDI (Biomarker-based Heuristic Engine for Dengue Identification) is a computational tool designed for the identification of Dengue virus serotypes in wastewater next-generation sequencing data.
PANDORA - Predictive Analytics aNd Data Oriented Research Applications 💻
A prediction-based extension of network-based statistics.
OmicSelector - Environment, docker-based application and R package for biomarker signiture selection (feature selection) & deep learning diagnostic tool development from high-throughput high-throughput omics experiments and other multidimensional datasets. Initially developed for miRNA-seq, RNA-seq and qPCR.
Univariate conditional average treatment effect estimation for predictive biomarker discovery
This package contains a Rshiny webtool developed to allow the calculation of the metabolic predictors developed by the groups of MOLEPI and LCBC (LUMC), from raw Nightingale Health 1H-NMR metabolomics data.
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