Open Source Python Bio-Informatics Software - Page 16

Application to optimize DNA sequences coding protein to put in in the different organizm (f.e. human protein in E.Coli). It proposes the optimal cutting places to connect many shorter fragments into bigger one using ligaze.

This is a pure Python CGI-based implementation of a taxonomically intelligent species search engine. It searches biological databases for a taxonomic name. The search is done "on the fly" using web services (SOAP/XML) or URL API's.

Application to create 'electronic fluorescent pictographic' representations of gene expression patterns. Created at the Provart lab of the department of Cell & Systems Biology, University of Toronto.

Epidaurus is a collection of epigenetic datasets including transcription factor ChIP-seq, histone ChIP-seq, DNase-seq, FAIRE-seq, DNA methylation, etc. It also includes commonly used genome features (GC content, conservation) and RNA-seq. A user friendly interface has been developed to interrogate and visuzlize these datasets.

Esra is a 100% pure java library for the interactive analysis of molecular mechanics data. Mangles your data in your favorite scripting language.

This project is started out of the idea to simulate simple creatures like game of live. The goal is to build up an multi processor/host environment to simulate the building of simple live in given world environments.

Simple python code that produces color-coded quality plots based on fastq format read quality scores. Scores are averaged over binned read tile coordinates. Useful for spotting spatial quality patterns.

Genome coverage, the number of sequencing reads mapped to a position in a genome, is an insightful indicator of irregularities within sequencing experiments. While the average genome coverage is frequently used within algorithms in computational genomics, the complete information available in coverage profiles (i.e. histograms over all coverages) is currently not exploited to its full extent. Thus, biases such as fragmented or erroneous reference genomes often remain unaccounted for. Making this information accessible can improve the quality of sequencing experiments and quantitative analyses. fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147

fqms is a software tool for Lable-free Quantification of Proteins by LCMSE.

geostd is an open-source set of restraints for molecules involved in macromolecular structure refinement. The restraints reduce the number of variables making the solution of protein structures a more tractable process.

go2Sim measures semantic similarity between genes annotated with Gene Ontology terms. Resnik and Wang methods supported. A new improvement of the methods is currently in development, it will be available as soon as the results have been published.

Tandem mass spectral peptide identification and validation software, similar to X!Tandem, OMSSA, MyriMatch. Suitable for single hosts through large clusters. Written in Python for simplicity, with performance-critical sections in C++.

a cross-platform framework and environment for haplotype analysis with a special focus on human and medical genetics in python/wxpython

This software detects homologous recombination events (HREs) from SNP data. Based on SNP alleles calls and locations, it breaks the genomes into locally colinear blocks, and looks for cases where SNPs do not agree with the vertical pattern of inheritance in a phylogeny. It applies a dynamic programming algorithm to model whether changes within a block are likely a result of mutations, sequencing errors, or HRE. We use information from the nearby SNPs, so that if 1-2 alleles in a series of SNPs differs from the ancestral allele, it may be better explained as a mutation or sequencing error. But if a series of SNP alleles differ from the ancestral pattern, then it may be more likely that an HRE has occurred, particularly if the allele pattern matches that from another part of the tree better than that of the ancestral node.

Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular pipeline, called iMir, integrating multiple open source modules and resource in an automated workflow, devising different statistical approaches to analyze data rigorously. iMir comprises also a Graphical User Interface (GUI), so that the pipeline is particularly suited for biologist and early stage bioinformaticians and produces both graphics and text outputs.

Python program devoted to study the relationship between cells during inmune response. It is based on a 3D periodic boundary conditions grid where cells see each other and react according to certain movement, growth and interaction rules.

lr2rmats is a Snakemake-based light-weight pipeline which is designed to utilize both third-generation long-read and second-generation short-read RNA-seq data to generate an enhanced gene annotation file. The newly generated annotation file could be provided to rMATS for differential alternative splicing analysis. More information can be found at https://sourceforge.net/p/lr2rmats/wiki/Home/

Development moved to: https://bitbucket.org/rongchenlab/malty Docs moved to: http://malty.readthedocs.org/en/latest/

This collection of tools forms the basis of a pipeline for the complete enumeration of the number of solutions present in a model that maximizes a single objective function.

metaProt is a python pipeline to analyze and extract data from protein sequences found in metagenomic projects. It integrates several existing tools (HMMer, Pepstats, Blast...) to be used against custom databases. Please, read the README.txt file to find more about this.

Metmask has moved to github http://github.com/hredestig/metmask Metmask is a tool written in python for managing chemical identifiers for metabolomics experiments. It can incorporate identifiers from local textfiles, several online databases, query PubChem and record all found associations in a local sqlite database.

miRPV is an Automated tool that allows users to predict and validate microRNA from genome/gene sequence. System Requirement CPU: AMD64 (64bit) Memory: 2Gb RAM Storage: 5Gb Ubuntu 18.04

mitoMaker is a pipeline script developed to simplify the assembly and automatic annotation of mitochondrial genomes, based on raw NGS reads and an optional target reference. mitoMaker calls well known assemblers and algorithms, such as SOAPdenovo, MIRA and blast+ and parses their results providing easily readable outputs, such as FASTA, GENBANK, SEQUIN, PNG and others. General pipeline: 1-iterative De Novo assembly, with different k-mer values, trying to assemble a build that matches a target mitochondrial genome given. 2-searches for all mitochondrial gene features and circularization. 3-stores the best result found. 4-uses the best assembly as backbone for a reference based assembly, using MIRA and MITObim, trying to extend the mitogenome and close gaps. 5-annotates the best assembly, identifying the start and end position of each and every feature. 6-creates a folder with all the results (PNG, GENBANK, FASTA, SEQUIN, CAF, MAF and a stats logfile).