Materials on the analysis of microarray expression data; focus on re-analysis of public data ( http://tinyurl.com/cruk-microarray)

Deep learning methods for feature selection in gene expression autism data.

Bioinformatics course project - Fall 2020, analysis of genetic expression omnibus (GEO) data series of Acute Myeloid Leukemia

Collection of gene expression datasets

Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.

A visualization support tool for advanced hierarchical clustering analysis. MLCut allows cutting dendrograms at multiple heights/levels. In other words, it allows to set multiple local similarity thresholds in potentially large dendrograms. It uses two coordinated views, one for the dentrogram (radial layout), and another for the original multidimensional data (parallel coordinates). The purpose is to add flexibility and enforce transparency in the process of selecting branches that correspond to the different clusters, while enabling the discovery of visual patterns in the original data.

An Efficeint and Fast Wrapper-based High-dimensional Feature Selection(SIFE) in MATLAB

A python library to develop genomic data simulators

Discriminant Analysis with Network PROcessing

NOWAC data cleaning package

Generating expression signatures for disease using STARGEO

Scripts using GEOquery package to fetch expression matrices and phenotypic data associated with GSE datasets

Transform, query, and merge tabular files with the expressionable Python module. This tool is used primarily for gene-expression data.

protGear is a package for protein microarray data processing just before the main analysis.

This R script is used to analyze microarray data acquired by an Agilent SureScan Microarray Scanner.

Code for the future "Classification of microarray data" paper.

Various python programs I use for the manipulation of SNP genotype datasets and other bioinformatics tasks. This repository features miscellaneous scripts to help work efficiently in common bioinformatics tasks I encounter. Use at own risk

TriCluster and microCluster gene expression clustering algorithms

MicAff is a genomic data analysis tool. Application made with Shiny. It is used to analyze the data from the microarray experiment. Running on a local server, it allows you to load CEL data, their initial processing and further analysis.

A structural equation modeling approach for the identification of gene expression adaptation in breast cancer patients at grade specific level

Code for my master thesis: "Microarray data analysis in prediction of breast cancer metastasis"

No description provided.

EXIS is an interactive R shiny application for isoform-specific expression analysis.

Selection of genes to be cultured and studied on-board for the AcubeSAT nanosatellite project. Microarray data analysis in R. Meta-analysis in R. Literature review and more

Metadata used to process Illumina Infinium DNA methylation data with pylluminator

A short pipeline for predicting acute myeloid leukemia (AML) in RNA microarray data

This is a final group project for Computational Biology (CS167) implementing Tempo (http://bcb.cs.tufts.edu/tempo/) on a unique Parkinson's dataset. This project was contributed to equally by Kevin Kapner, Carlos Lopez-Rodriguez, and Qing Zhu.

Differential expression analysis using R :dna:

Use Deep Learning Methods to analyze gene based microarray data to make classifcations on diseases, especially cancers, where the model is going to identify cancer stages for different cancers.

GEO microarray data analysis