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A directory of tools, AI models, datasets, and research resources for biotech, bioinformatics, and other scientific fields. Aggregated from curated GitHub awesome-lists, HuggingFace, bio.tools, Bioconductor, and more.
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19 of 5,893 resources
Provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform.
Gene Set Enrichment Analysis of P-value based statistics for outlier gene detection in dataset merged from multiple studies
It fits correlation motif model to multiple studies to detect study specific differential expression patterns.
Tools for export and import classification trees and clusters to other programs
Package for assessing the statistical significance of periodic expression based on Fourier analysis and comparison with data generated by different background models
This package provides a supervised technique able to identify differentially expressed genes, based on the construction of \emph{Fuzzy Patterns} (FPs). The Fuzzy Patterns are built by means of applying 3 Membership Functions to discretized gene expression values.
This package contains functions for reading raw data in ImaGene TXT format obtained from Exiqon miRCURY LNA arrays, annotating them with appropriate GAL files, and normalizing them using a spike-in probe-based method. Other platforms and data formats are also supported.
Analysis of array CGH data : detection of breakpoints in genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified.
Wraper functions for description/comparison of oligo ID list using Gene Ontology database
A Method to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set
Importation, normalization, visualization, and quality control functions to correct identified sources of variability in array-CGH experiments.
This package implements the classification pipeline of the best overall team (Team221) in the IMPROVER Diagnostic Signature Challenge. Additional functionality is added to compare 27 combinations of data preprocessing, feature selection and classifier types.
The Mfuzz package implements noise-robust soft clustering of omics time-series data, including transcriptomic, proteomic or metabolomic data. It is based on the use of c-means clustering. For convenience, it includes a graphical user interface.
Functions for normalisation of two-color microarrays by optimised local regression and for detection of artefacts in microarray data
SpikeLI is a package that performs the analysis of the Affymetrix spike-in data using the Langmuir Isotherm. The aim of this package is to show the advantages of a physical-chemistry based analysis of the Affymetrix microarray data compared to the traditional methods. The spike-in (or Latin square) data for the HGU95 and HGU133 chipsets have been downloaded from the Affymetrix web site. The model used in the spikeLI package is described in details in E. Carlon and T. Heim, Physica A 362, 433 (2006).
This package facilitates reading, preprocessing and manipulating Codelink microarray data. The raw data must be exported as text file using the Codelink software.