<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/30216?offset=170 https://bioinformaticsonline.com/bookmarks/view/27110/easyfig Fri, 29 Apr 2016 05:49:39 -0500 https://bioinformaticsonline.com/bookmarks/view/27110/easyfig <![CDATA[Easyfig]]> Easyfig has moved to github, for newer releases of Easyfig please visit our new webpage - https://mjsull.github.io/Easyfig.  Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface (GUI).

More at http://easyfig.sourceforge.net/

Address of the bookmark: http://easyfig.sourceforge.net/

]]> Poonam Mahapatra https://bioinformaticsonline.com/bookmarks/view/27035/spades Tue, 19 Apr 2016 08:37:08 -0500 https://bioinformaticsonline.com/bookmarks/view/27035/spades <![CDATA[SPAdes]]> SPAdes – St. Petersburg genome assembler – is intended for both standard isolates and single-cell MDA bacteria assemblies. This manual will help you to install and run SPAdes. SPAdes version 3.7.1 was released under GPLv2 on March 8, 2016 and can be downloaded from http://bioinf.spbau.ru/en/spades.

Manual at http://spades.bioinf.spbau.ru/release3.7.1/manual.html

Address of the bookmark: http://bioinf.spbau.ru/spades

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/27104/gatb-genome-analysis-toolbox-with-de-bruijn-graph Thu, 28 Apr 2016 11:16:51 -0500 https://bioinformaticsonline.com/bookmarks/view/27104/gatb-genome-analysis-toolbox-with-de-bruijn-graph <![CDATA[GATB : Genome Analysis Toolbox with de-Bruijn graph]]> The Genome Analysis Toolbox with de-Bruijn graph (GATB) provides a set of highly efficient algorithms to analyse NGS data sets. These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (e.g. metagenomes).

More at https://gatb.inria.fr/

Address of the bookmark: https://gatb.inria.fr/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/27818/gaemr Tue, 14 Jun 2016 06:18:37 -0500 https://bioinformaticsonline.com/bookmarks/view/27818/gaemr <![CDATA[GAEMR]]> The Genome Assembly Evaluation Metrics and Reporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR’s analysis pipeline, hence enabling the generation of standard reports.

GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly. 

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/

]]> Jit https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel Fri, 30 May 2014 13:24:11 -0500 https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel <![CDATA[How to sequence the human genome - Mark J. Kiel]]> View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence. Lesson by Mark J. Kiel, animation by Marc Christoforidis.]]> https://bioinformaticsonline.com/news/view/19090/deeptools Sat, 08 Nov 2014 15:02:08 -0600 https://bioinformaticsonline.com/news/view/19090/deeptools <![CDATA[deepTools]]> deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.

Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full

Source Code and Wiki: https://github.com/fidelram/deepTools/wiki

Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools

and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows

]]> Martin Jones https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems Thu, 18 Dec 2014 10:32:48 -0600 https://bioinformaticsonline.com/bookmarks/view/19631/rosalind-bioinformatics-problems <![CDATA[Rosalind Bioinformatics problems !!!]]> Rosalind is a platform for learning bioinformatics and programming through problem solving. Take a tour to get the hang of how Rosalind works.

http://rosalind.info/problems/list-view/

Address of the bookmark: http://rosalind.info/problems/list-view/

]]> Abhi https://bioinformaticsonline.com/researchlabs/view/19648/mit-computational-biology-group Thu, 18 Dec 2014 14:47:01 -0600 <![CDATA[MIT Computational Biology Group]]> My research group consists primarily of computer science graduate students and postdocs with expertise in algorithms, statistical inferences and machine learning, and sharing a passion for understanding fundamental biological problems.

We work in a highly interdisciplinary environment at the interface of Computer Science and Biology. Since its inception, our lab has eagerly engaged in collaborative research partnerships with biological and experimental collaborators, facilitated by our affiliation with the Broad Institute and the Computational and Systems Biology initiative (CSBi) at MIT, our participation in the Epigenome Roadmap, ENCODE, and modENCODE consortia, and by several other ongoing collaborations at MIT, Harvard, and the Harvard Medical School affiliated hospitals.

http://compbio.mit.edu/

]]> https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d Thu, 25 Dec 2014 23:14:52 -0600 https://bioinformaticsonline.com/bookmarks/view/19786/shrec3d <![CDATA[ShRec3D]]> ShRec3D is a program that aims at reconstructing a genome 3D structure (b) from the sole knowledge of the contacts between different genomic regions (a) as determined by Hi-C (http://www.ncbi.nlm.nih.gov/pubmed/19815776).

There are two options to run ShRec3D (on linuX only so far): the first one uses the Matlab complier runtime environment (MCR), the second one doesn't need any other library to be installed but only works with the latest versions of Linux (equivalent to Fedora 19 and above).

Address of the bookmark: https://sites.google.com/site/julienmozziconacci/#TOC-Downloads

]]> Jitendra Narayan https://bioinformaticsonline.com/researchlabs/view/22410/nicolas-corradi-lab Tue, 26 May 2015 16:19:02 -0500 <![CDATA[Nicolas Corradi Lab]]> The goal of our research is to better understand the biology of microbial organisms of significant ecological, veterinary and medical importance.
To achieve this goal, our team combines the power of next generation DNA sequencing and bioinformatics with molecular biology and experimental procedures.

Main research topics:
- Comparative and Population Genomics of Plant Symbionts
- Parasite Genome Evolution
- Experimental Evolution of Microbial Symbionts and Parasites
- Phylogenomics of Early Branching Fungi

More at http://corradilab.weebly.com/

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