Open Source Python Bio-Informatics Software - Page 7
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Python Bio-Informatics Software
View 66 business solutionsBrowse free open source Python Bio-Informatics Software and projects below. Use the toggles on the left to filter open source Python Bio-Informatics Software by OS, license, language, programming language, and project status.
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ENLY
Bioinformatic tool to improve draft genome assemblies by closing gaps
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EUtils is a python client-side library for querying the NCBI's Entrez life science databases through the NCBI eUtils web services.
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EducationalLCS
eLCS - Educational Learning Classifier System
Educational Learning Classifier System (eLCS) is a set of learning classifier system (LCS) educational demos designed to introduce students or researchers to the basics of a modern Michigan-style LCS algorithm. This eLCS package includes 5 different implementations of a basic LCS algorithm, as part of a 6 stage set of demos that will be paired with the first introductory LCS textbook. Each eLCS implementations (from demo 2 up to demo 6) progressively add major components of the entire LCS algorithm in order to illustrate how work, how they are coded, and what impact they have on how an LCS algorithm runs. The Demo 6 version of eLCS is most similar to the UCS algorithm. Each version only includes the minimum code needed to perform the functions they were designed for. This way users can start by examining the simplest version of the code and progress forward. This code is intended to be used as an educational tool, or as algorithmic code building blocks. -
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Erda
Workflow automation of Thomas networks
This script is supplementary to the article "Time series dependent analysis of unparametrized Thomas networks" and performs the workflow steps described in section 7. -
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ExAM-Exome_Analysis_And_Mining
A whole exome sequencing analysis package and its graphical interface
During the past few years, whole exome sequencing has imposed itself for genetic research, largely due to its use for detection of causative mutations responsible for Mendelian disorders. As a consequence of their power and of the rapidly decreasing cost of these technologies, massive amount of exome sequencing data are generated and becoming available to a broadening community of scientists. However, these data remain difficult to analyze and interpret by the general scientific community, due to the limited bioinformatics resources that are currently freely available for their analysis and the partial information that they provide. Here, we present an interactive and free analysis package, ExAM, dedicated to whole exome sequencing data analysis. It is accessible to non-computer scientists and provides a complete set of information, as well as decision support to prioritize candidate disease causing variants. -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ExSTraCS combines a number of recent advancements into a single algorithmic platform. It can flexibly handle (1) discrete or continuous attributes, (2) missing data, (3) balanced or imbalanced datasets, and (4) binary or many classes. A complete users guide for ExSTraCS is included. Coded in Python 2.7. -
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FONZIE is a bioinformatic tool written in Python developed for the genetic cartography speciality. FONZIE allow as well to find markers on a set of sequences than to find associate oligonucleotides. http://www.biomedcentral.com/1756-0500/3/322/abstra
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FaceIn! is a face recognizing log in application for Linux. You will never have to enter your password anymore! Just show your face to your camera and let the system recognize you and take you to your desktop!
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Tools for comparative sequence analysis. Includes FamilyRelations (GUI) and a C++ toolkit/Python wrapper for doing fixed-width-window analyses.
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This is a Python-based efficient implementation of several semantic similarity measures. The target is to enable fast and easy calculation of similarity between proteins and genes using the Gene Ontology (GO).
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These scripts written in Python allow you to convert fasta files into multifasta file and vice versa.
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Fastq-Fasta Converter
A bioinformatics tool that converts Fastq into Fasta
Fastq-Fasta Converter is a desktop application that converts Fastq files into Fasta files. -
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A database and a web front end for physiologic data on animal feeding, developed with PostgreSQL and Django at NESCent (http://www.nescent.org) for Mammalian Feeding Working Group (http://www.feedexp.org). Current development of the codebase is on Github at http://github.com/NESCent/feedingdb.
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FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
FineSplice is a Python wrapper to TopHat2 geared towards a reliable identification of expressed exon junctions from RNA-Seq data, at enhanced detection precision with small loss in sensitivity. Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. Potential false positives arising from spurious alignments are filtered out via a semi-supervised anomaly detection strategy based on logistic regression. Multiple mapping reads with a unique location after filtering are rescued and reallocated to the most reliable candidate location. FineSplice requires Python 2.x (>= 2.6) with the following modules installed: pysam (http://code.google.com/p/pysam/) and scikit-learn (http://scikit-learn.org/). For further details check out our publication: Nucl. Acids Res. (2014) doi: 10.1093/nar/gku166 -
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FingerID
Metabolite identification via machine learning.
[NOTICE!] FingerID since version 1.4 will be hosted on github: https://github.com/icdishb/fingerid A metabolite identification software using tandem mass spectrometry and kernel methods. The related paper can be found at http://bioinformatics.oxfordjournals.org/content/early/2012/07/18/bioinformatics.bts437.abstract. Now it supports unix/linux like system. -
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FlexGrePPS forms the foundation of a novel antigenic screening methodology that is based on the representation of an entire proteome by near-optimal degenerate peptide pools.
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Flow Investigation using N-Dimensions (FIND) is a program designed for analysis and visualization of Flow Cytometry data. FIND focuses specifically on automated population discovery (clustering) methods. The project targets both users and developers.
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GASiC
Genome Abundance Similarity Correction
One goal of sequencing based metagenomic analysis is the quantitative taxonomic assessment of microbial community compositions. However, the majority of approaches either quantify at low resolution (e.g. at phylum level) or have severe problems discerning highly similar species. Yet, accurate quantification on species level is desirable in applications such as metagenomic diagnostics or community comparison. GASiC is a method to correct read alignment results for the ambiguities imposed by similarities of genomes. It has superior performance over existing methods. You can find the accompanying paper here: http://nar.oxfordjournals.org/content/41/1/e10.short Thanks to the great work of the SeqAn team, you can now use GASiC as a Knime workflow: https://github.com/seqan/knime_seqan_workflows/tree/master/metagenomics_gasic_workflow -
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GCB_package
Stand-alone version of the Genome Complexity Browser
This application allows observing genome rearrangements in prokaryotic genomes. It provides rearrangements frequencies profiles and genomes graph representation. -
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GIIAF Microscopy Library
The GIIAF Microscopy Library, that uses customised OMERO software
This project incorporates a suite of tools that aim to allow researchers within Griffith's Imaging and Image Analysis Facility (GIIAF) to efficiently and effectively provide secure, centralised, web-accessible data storage, management and manipulation. The open-source Java-based OMERO software was customised to provide most of the features of this project. -
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Genetic programming environment to inference context free grammars base on positive and negative examples of language.
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GS junior Webserver
GS junior Webserver
GS junior Webserver is a web based file server to easily access sequencing data of -
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GWCNV is a genome-wide algorithm for detecting CNV associations with diseases. It works directly on a transformation of intensity data. It is powerful and sensitive in detecting small CNV associations, and retains high power for large CNVs.
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Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The
