Open Source Python Bio-Informatics Software - Page 10

We developed a novel clustering-free method, microarray-associated motif analyzer (MAMA), to predict novel cis-acting elements based on weighted sequence similarities and gene expression profiles in microarray analyses. Simulation of gene expression was performed using a support vector machine and based on the presence of predicted motifs and motif pairs. The accuracy of simulated gene expression was used to evaluate the quality of prediction and to optimize the parameters used in this method. After optimization, MAMA accurately simulated more than 87% of gene expression. See Kakei Y, Ogo Y, Itai RN, et al. (2013) Development of a novel prediction method of cis-elements to hypothesize collaborative functions of cis-element pairs in iron-deficient. Rice 6(1): 22.

MicrobeGPS is a bioinformatics tool for the analysis of metagenomic sequencing data. The goal is to profile the composition of metagenomic communities as accurately as possible and present the results to the user in a convenient manner. One main focus is reliability: the tool calculates quality metrics for the estimated candidates and allows the user to identify false candidates easily.

XMIPP is an image processing suite for 3D-reconstruction of biological specimens from transmission electron microscopy data. NOTE that stable releases (including binaries) are longer stored at Sourceforge, but are available at http://xmipp.cnb.csic.es

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length. Please note that Mix has moved to: https://github.com/massyah/MIX

Graphical interface for ModelTest and MrModelTest written in Python, for Windows, Linux and Mac OSX

Moose is the core of a modern software platform for the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, large networks, and systems-level processes. We have moved Github.com. This should be your source for the latest version of the code.

A text mining system for extraction of protein-protein interactions from biomedical text.

MutaNET comes with a next generation sequencing (NGS) pipeline that calls mutations based on paired-end NGS reads, an automated mutation analysis tool and various file converters and mergers. The mutation analysis feature considers the coding region, protein domains, regulation and transcription factor binding site information, and can be used to analyse the potential impact of mutations on antibiotic resistance.

The NMR Restraints Grid (NRG at http://www.bmrb.wisc.edu/WebModule/MRGridServlet) contains the original NMR restraint data (distance, dihedral angle and RDC) and the parsed, converted, and filtered for ~4,000 protein and nucleic acid structures with corr

Naimath (syn. blessing) is a project to create tools for diagnosis, management of clinical cases in the form of Rule based Medical Expert System integrating Interactive Health education, Semantified EMR, and serve as a learning tool for students. Website seen at www.naimath.com

NetBuilder' is a tool for building, visualizing, and simulating multi-layered biological networks, structured as hierarchical Petri-nets. It has a built-in stochastic simulator, but also provides easy access to other simulation and analysis.

NetView P has been re-structured as a package for R and moved to GitHub: https://github.com/esteinig/netview

Network Visualization is a mature part of computer science that is enjoying a good deal of growth, partially fueled by Bioinformatics. Network is a synonym for Graph, and both refer to a collection of nodes and edges.

NeuraPy is now hosted on github This is a collection of Python modules that read files encountered in neuroscience experiments. Included are modules to read lablib files and modules to read Cyberkinetics Cerebus system .nev and .ns3 files

Simulator of virtual animals made up of biological neural networks for research in the Computational Neuroscience field.

NeuroPython is a Python module created for easy simulation of neural networks.

NumericalFISH is a bioinformatics graphical tool for easy analysis of BLAST or BLAT results, especially aimed at the study of duplications or segmental duplications.

An open source implementation of a protein threading program based on the energy functions and techniques originally introduced by Prospect.

The purpose of this project is to make available a variety of tools written in Python.

Bisulfite sequencing (BSseq) processing is among the most cumbersome next generation sequencing (NGS) applications. Though some BSseq processing tools are available, they are scattered, require puzzling parameters and are running-time and memory-usage demanding. We have developed P3BSseq, a parallel processing pipeline for fast, accurate and automatic analysis of BSseq reads that trims, aligns, annotates, records the intermediate results, performs bisulfite conversion quality assessment, generates BED methylome and report files following the NIH standards. P3BSseq outperforms the known BSseq mappers regarding running time, computer hardware requirements. We optimized the P3BSseq parameters for both directional and non-directional libraries, and for both single-end and paired-end reads of Whole Genome and Reduced Representation BSseq. P3BSseq is a user-friendly streamlined solution for BSseq upstream analysis, requiring only basic computer and NGS knowledge.

PARs is a bioinformatics tool for the analysis of cis-regulatory DNA sequences. Composed of two parts: a suite of sequence analysis algorithms for predicting cis-binding sites in DNA sequences and a GUI for visualisation and exploration of the results.

Physiologically based toxicokinetic (PBTK) modeling offers great promise in environmental risk assessment, potentially speeding up dose-response studies while minimizing animal testing. Some limitations exist in the PBTK field, such as difficulty of model development and a lack of application specific software tools to help modelers. Some parameters used in PBTK models, such as tissue weights, are easily measure. Other parameters can be determined through in-vitro experiments or through extrapolation using published equations. When it is impractical to use these methods to estimate a parameter, techniques can be used to optimize parameters so that model results best fit validation data. This tool was designed to optimize a user-specified list of parameters to a user-specified PBTK model. The user also controls validation data and optimization algorithms. In addition to optimized parameters, the tool outputs statistical information about the fit of the optimized model.

This software has moved to http://www.poissonboltzmann.org/

This software tool assists in the identification of PLGS identified peptides that provides high quality HDX information. The output file is formated so it can be directly imported into DynamX. This tool requires that the user has python installed.

PPLine is a Python-based suite aimed to process raw RNA-seq or Exome-seq data. PPLine provides: - read mapping (STAR/Tophat2/bowtie/bowtie2), including novel splice junsctions discovery - gene and transcript expression estimation (HTSeq-count/Cufflinks) - SNP calling with BQSR and indel realignment (samtools/GATK) - variant annotation (Annovar) - novel transcripts discovery (Cufflinks) - predicting proteotypic peptides and creating ref/alt proteins fasta-database - integration of the results