BOL: Related items

MafTools

Jit — Thu, 16 Feb 2017 11:16:01 -0600

maftools - An R package to summarize, analyze and visualize MAF files. Introduction.

With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. The Cancer Genome Atlas Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The resulting data consisting of genetic variants is stored in the form of Mutation Annotation Format. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.

maftools is on bioRxiv

Please cite the below if you find this tool useful for you.

Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: http://dx.doi.org/10.1101/052662

Address of the bookmark: https://github.com/PoisonAlien/maftools

Salzberg lab

Mon, 15 May 2017 05:14:01 -0500

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.

https://salzberg-lab.org/

Senior Bioinformatics Software Developer, Hyderabad, Telangana

Mon, 03 Jul 2017 10:10:31 -0500

DuPont Pioneer is the world leader in plant biotechnology area including discovery, development and delivery of elite crop genetics. DuPont Pioneer is aggressively building Big Data and Predictive Analytics capabilities in order to deliver improved services to our customers. We are currently seeking Senior Bioinformatics Software Developer at the DuPont Knowledge Center in Hyderabad, India for our global Data Science and Informatics group. At DuPont Pioneer, you’ll become part of a work environment that nurtures your interests, ignites your passion, creates opportunities to serve and helps you attain success–both personally and professionally. The hiring level will be commensurate with the level of experience. This is a critical position with the potential to make immediate, significant impact on our business.
The successful candidate will have an extensive background in computer science and bioinformatics through courses or academic degrees, and proven experience in bioinformatics software development. We are looking for those creative, smart, model driven, agile individuals who enjoy giving their all to tackle diverse software needs.
Duties / Responsibilities

Job Qualifications
Education and Experience
• Master Degree in Bioinformatics, Computational biology, Scientific Computing or related field
• 3-5 years of Post-Master’s experience in Bioinformatics software development
• Proven experience developing high throughput bioinformatics applications
Required Competencies
• Strong proven experience in Python programming language in Linux environment
• Proven High Performance computing experience (LSF/SGE/OGE)
• Exposure in code versioning and repository management (GIT/SVN)
• Proven experience in Bioinformatics algorithm development
• Deep understanding in Bioinformatics tools, data types
Desired Competencies
• Familiarity working in a scientific computing environment (NumPy, SciPy, Pandas etc.)
• Familiarity working with Cloud technologies (AWS, Azure)
• Ability to demonstrate solid analytical skills and exceptional attention to detail.
• Experience in relational databases and data structures
• Proven experience working with teams using agile software development methodologies and processes
• Familiarity with Service Oriented Architecture (SOA)
• Familiarity with build tools (Jenkins, make, ANT, Maven)
• Exposure to project management tools (JIRA, Confluence, RED MINE, etc.)

More at http://careers.dupont.com/jobsearch/job-details/senior-bioinformatics-software-developer/012939W-01/

Bioinformatics tools developed for Oxford Nanopore data analysis !

biogeek — Wed, 27 Dec 2017 20:47:30 -0600

MinION is the only portable real-time device for DNA and RNA sequencing. Each consumable flow cell can now generate 10–20 Gb of DNA sequence data. Ultra-long read lengths are possible (hundreds of kb) as you can choose your fragment length. One of the technical advantages of ONT data is the read length, which offers great prospects for genome assembly. Generally, assemblers are based on several different types of algorithms, such as greedy, overlap-layout-consensus (OLC), de Bruijn graph (DBG), and string graph.

List of analysis tools developed for Oxford Nanopore data

BWA
Fast nanopore data tuned alignment tool
https://github.com/lh3/bwa

GraphMap
Mapper for long and error-prone reads
https://github.com/isovic/graphmap

LAST
Nanopore tuned alignment tool
http://last.cbrc.jp/

LINKS
Software tool for long read scaffolding
https://github.com/warrenlr/LINKS/

marginAlign
Tools to align nanopore reads to a reference
https://github.com/benedictpaten/marginAlign

minoTour
Real time analysis tools
http://minotour.nottingham.ac.uk/

nanoCORR
Error-correction tool for nanopore sequence data
https://github.com/jgurtowski/nanocorr

NanoOK
Software for nanopore data, quality and error profiles
https://documentation.tgac.ac.uk/display/NANOOK/NanoOK

Nanopolish
Nanopore analysis and genome assembly software
https://github.com/jts/nanopolish

nanopore
Variant-detection tool for nanopore sequence data
https://github.com/mitenjain/nanopore

Nanocorrect
Error-correction tool for nanopore sequence data
https://github.com/jts/nanocorrect/

npReader
Real-time conversion and analysis of nanopore reads
https://github.com/mdcao/npReader

poRe
Tool for analyzing and visualizing nanopore data
https://sourceforge.net/p/rpore/wiki/Home/

PoreSeq
Error-correction and variant-calling software
https://github.com/tszalay/poreseq

Poretools
Nanopore sequence analysis and visualization software
https://github.com/arq5x/poretools

SSPACE-LongRead
Genome scaffolding tool
http://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE-longread

SMIS
Genome scaffolding tool
https://sourceforge.net/projects/phusion2/files/smis/

List of assemblers for Oxford Nanopore MinION long reads

LQS
DALIGNER, Celera OLC Nanocorrect,
Nanopolish corrector
https://github.com/jts/nanopolish

PBcR
HGAP or BLASR, Celera OLC
PBcR corrector
http://wgs-assembler.sourceforge.net/wiki/index.php/PBcR
–
Canu
MHAP, Celera OLC
Canu corrector
https://github.com/marbl/canu

Falcon
String graph, Celera OLC
Falcon corrector
https://github.com/PacificBiosciences/falcon

Miniasm
OLC
https://github.com/lh3/miniasm

ra-integrate
OLC
https://github.com/mariokostelac/ra-integrate/

ALLPATHS-LG
de Bruijn graph
ALLPATHS-L corrector
https://www.broadinstitute.org/software/allpaths-lg/blog/?page_id=12

SPAdes
de Bruijn graph
SPAdes corrector
http://bioinf.spbau.ru/spades

Binding Site Prediction in Protein !

Poonam Mahapatra — Wed, 25 Apr 2018 04:35:57 -0500

The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).

Pockets Identification

CASTp

Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin

Pocket-Finder

Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.

PocketPicker

Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for PyMOL

Binding Site Prediction

ConSurf

Identification of functional regions in proteins by surface-mapping of phylogenetic information

CRESCENDO

Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.

Ligand Binding Sites

3DLigandSite

The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.

FINDSITE

A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.

LIGSITE^csc

Prediction of binding site by pocket identification using the Connolly surface and degree of conservation

metaPocketA meta server for ligand-binding site prediction. metaPocket use LIGSITE^csc, PASS, Q-SiteFinder and SURFNET

Research Associate Bioinformatics in IISc Recruitment 2020

Tue, 23 Jun 2020 21:53:34 -0500

Research Associate Bioinformatics in IISc Recruitment 2020

Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.

Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.

Desirable Qualifications (Research Associate/s): i) Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment).

ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv) Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.

The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.

Emoluments: As per DST, GOI norms and commensurate with experience.

More at https://www.iisc.ac.in/positions-open/

Anders Krogh Lab

Mon, 30 Sep 2013 19:07:40 -0500

In a lot of my work in bioinformatics, I have been using hidden Markov models (HMMs). As a postdoc with David Haussler at UCSC we developed the so-called profile HMMs (refs). Since then I have applied HMMs to membrane proteins (refs) and gene identification (refs) and have worked on methods for such things as discriminative estimation of HMMs (refs) and alternative decoding algorithms etc. (refs).

Now my main interests are in gene regulation, where we work on promoter analysis; non-coding RNA, where miRNAs and structure prediction are the main areas; and protein structure, where the group is working on methods for structure prediction from sequence. To read more about these topics, please see the research pages.

Lab page @ http://wiki.binf.ku.dk/User:Krogh

lsugenomics Lab

Thu, 07 Jul 2022 05:26:37 -0500

In our lab, we seek to characterize and to compare genomes in order to better understand genetic and evolutionary processes linking genotypes to phenotypes.

Sequencing and decoding plant genomes have been integral in our approaches.

The overarching goal of our research is to understand how to interpret complex and fascinating messages embedded in genomes.

https://www.lsugenomics.org/

CRCRI Bioinfomatics Walk In on 08.10.2013

Fri, 27 Sep 2013 10:59:53 -0500

Walk-in-Interview for recruitment of one Project Fellow for a period of 10 months purely on temporary basis is proposed to be held at Central Tuber Crops Research Institute, Sreekariyam, Thiruvananthapuram for a KSCSTE funded project entitled “PARTICIPATORY DEVELOPMENT OF A WEB BASED USER FRIENDLY CASSAVA EXPERT SYSTEM”

Salary: Rs. 10,000/- per month.

Age limit: 35 for men and 40 for women & SC/ST.

Qualification: First class in M. Sc (Agriculture)/MCA/M.Sc (IT)/ M. Sc (Computer Application)/M.Sc (Bioinformatics)/M.Sc (Geoinformatics).

Desirable: Two years experience in web design and web programming.

Date & time of interview: 08.10.2013, 10 am

Interested candidates may appear for an interview at this institute along with their application in plain paper containing the following particulars viz. (1) Name (2) Father/Husband/Guardian’s Name (3) date of birth & age as on 01.10.2013 (4) Permanent address (5) Address for communication (6) Email address and Telephone No. with code (7) Qualification (8) National fellowship like ICAR/CSIR/UGC etc. if any (9) Whether SC/ST/OBC (10) Details of experience (Attested copies of degree certificate, proof of age, mark sheets). Original certificates should be produced for verification.

No TA/DA will be admissible to the candidates attending the test. The selected candidate will have to join immediately.

Advertisement: http://www.ctcri.org/careers/mithra_SRF.doc

Bioinformatics Training Collections !

BioStar — Sun, 05 Mar 2023 23:01:26 -0600

Useful list of bioinformatics training collections @ https://github.com/sib-swiss/training-collection

Address of the bookmark: https://github.com/sib-swiss/training-collection