41 packages returned for Tags:"bioinformatics"

.NET Bio is an open source bioinformatics/genomics library for .NET Standard 2.0 that is designed to enable simple loading, saving and analysis of biological data. It includes several common parsers as well as... More information

Proyecto experimental para el estudio de biosecuencias en el grupo DESTINO

Open source bioinformatics and computational biology toolbox written in F#.

The common database reader includes: NCBI genbank reader NCBI gff/PTT feature sites document reader KEGG DBGET/LinkDB/BriteText/SSDB rest API MetaCyc database parser Common Fasta sequence database I/O DOOR... More information

ISA compliant experimental metadata toolkit in F#. This project is meant as an easy means to open, manipulate and save ISA (Investigation,Study,Assay) metadata files in the dotnet environment.

Statistical functions with a clear biological focus written in F#.

Read/write functions for various biological file formats

This library provides the NCBI blast+ output parser and some data analysis API, like SBH, BBH, venn diagram analysis. This package also provides a batch schedule extension for the large scale localblast... More information

Implementations of compression schemes for numeric data from mass spectrometers. Inofficial nuget package

Data visualization for bioinformatic purposes

imlp predicts iMTS-L propensity profiles of protein sequences of interest

Machine learning with BioFSharp and CNTK.Net.

Open source bioinformatics and computational biology toolbox written in F#.

Excel File IO methods for ISA compliant experimental metadata toolkit in F#. The underlying datamodel can be directly read from and written to ISA-Json and ISA-Excel (ISATab format) files.

Functional graph-library written in F#

Fable compliant release for the ISA compliant experimental metadata toolkit in F#. Additionally to the compiled library, it is shipped with the uncompiled code.

Bioinformatics in F#

TMEA (Thermodynamically Motivated Enrichment Analysis) is a thermodynamically motivated approach to gene set enrichment analysis

Package Description

Image recognition and analysis using wavelet transformations