BOL: Related items

Bioinformatics opening at ICGEB NEW DELHI

Thu, 02 Mar 2017 04:16:36 -0600

ICGEB NEW DELHI

Applications are invited for:

Junior Research Fellow, in a DBT funded project, is available in Translational Health Group, ICGEB, New Delhi

Qualifications:

Education: M.Sc. (preferably in Biotechnology, Life Sciences or Zoology, Chemistry, Bioinformatics). Candidates with hands on experience on GC-MS data acquisition and analysis will be given preference. Bioinformatics expertise required.

Fellowship: As per DBT guidelines.

Tenure: The position is purely on temporary basis with an initial tenure of six months and based on satisfactory performance may continue until the completion of the project.

Closing date for applications: 04/03/2017

Please send a "TWO PAGE" CV by email to: th.icgeb@gmail.com on or before the last date.

Research Associate, in a DBT funded project, is available in Translational Health Group, ICGEB, New Delhi

Qualifications:

Education: Ph.D. (in Biology, Biotechnology, Chemistry, Bioinformatics). Candidates with hands on experience on GC-MS data acquisition and analysis will be given preference.

Fellowship: As per DBT guidelines.

Tenure: The position is purely on temporary basis with an initial tenure of six months and based on satisfactory performance may continue until the completion of the project.

Closing date for applications: 04/03/2017

Please send a "TWO PAGE" CV by email to: th.icgeb@gmail.com on or before the last date.

LAMSA: fast split read alignment with long approximate matches

Jit — Tue, 15 May 2018 04:44:42 -0500

LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs). LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants. We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs. LAMSA is open source and free for non-commercial use. LAMSA is mainly designed by Bo Liu & Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.

Address of the bookmark: https://github.com/hitbc/LAMSA

Cactus: a reference-free whole-genome multiple alignment program

Jit — Mon, 12 Aug 2019 07:52:33 -0500

Cactus is a reference-free whole-genome multiple alignment program. The principal algorithms are described here: https://doi.org/10.1101/gr.123356.111

Cactus uses substantial resources. For primate-sized genomes (3 gigabases each), you should expect Cactus to use approximately 120 CPU-days of compute per genome, with about 120 GB of RAM used at peak. The requirements scale roughly quadratically, so aligning two 1-megabase bacterial genomes takes only 1.5 CPU-hours and 14 GB RAM.

Address of the bookmark: https://github.com/ComparativeGenomicsToolkit/cactus

The wavefront alignment (WFA) algorithm

BioStar — Sun, 28 Jun 2020 10:17:50 -0500

The wavefront alignment (WFA) algorithm is an exact gap-affine algorithm that takes advantage of
homologous regions between the sequences to accelerate the alignment process. As opposed to traditional dynamic programming algorithms that run in quadratic time, the WFA runs in time O(ns), proportional to the read length n and the alignment score s, using O(s^2) memory. Moreover, the WFA exhibits simple data dependencies that can be easily vectorized, even by the automatic features of modern compilers, for different architectures, without the need to adapt the code.

Address of the bookmark: https://github.com/smarco/WFA

A web-based tool for sequence alignment statistics and innovative visualization

BioStar — Thu, 04 Apr 2024 01:44:50 -0500

AlignStatPlot, a new R package and online tool that is well-documented and easy-to usefor MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analy-ses on sequencing data and generates new visualisation methods for MSA results. Whencompared to currently available tools, AlignStatPlot provides a robust ability to handle andvisualise diversity data, while the online version will save time and encourage researchersto focus on explaining their findings. It is a simple tool that can be used in conjunction withpopulation genetics software (PDF) AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data.

Address of the bookmark: https://bioinformatics.um6p.ma/AlignStatPlot/

JSON

Abhimanyu Singh — Tue, 04 Apr 2017 08:02:39 -0500

JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language, Standard ECMA-262 3rd Edition - December 1999. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language.

JSON is built on two structures:

A collection of name/value pairs. In various languages, this is realized as an object, record, struct, dictionary, hash table, keyed list, or associative array.
An ordered list of values. In most languages, this is realized as an array, vector, list, or sequence.

These are universal data structures. Virtually all modern programming languages support them in one form or another. It makes sense that a data format that is interchangeable with programming languages also be based on these structures.

Address of the bookmark: http://json.org/

Alvis: a tool for contig and read ALignment VISualisation and chimera detection

LEGE — Wed, 08 May 2024 07:02:55 -0500

Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in a variety of alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies.

More at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04056-0

Address of the bookmark: https://github.com/SR-Martin/alvis

Python vs Perl

Rahul Agarwal — Thu, 11 Jul 2013 14:39:19 -0500

Why bioinformatician still using Perl when Python is easy to code, good in ReXp and faster than perl?

Junior Research Fellow (JRF)

Sat, 13 Jul 2013 11:17:22 -0500

School of Biotechnology
Gautam Buddha University
Greater Noida, UP - 201310

Applications are invited for one position of Junior Research Fellow (JRF) in a Department of Biotechnology (DBT) sponsored research project entitled “Design, synthesis and evaluation of potent aminopeptidase inhibitors for malarial therapy” under the supervision of Dr. Shakti Sahi.

The monthly fellowship of JRF will be Rs 12,000/- plus HRA as per the University rules.

Essential Qualification: Master degree in any discipline of Life Science with NET qualified.

Desirable Qualification: Preference will be given to candidates having research experience in in silico drug designing/Bioinformatics.

Interested candidates may send their resume to undersigned on or before 14th July 2013 by post-mail/e-mail shaktis@gbu.ac.in or shaktisahi@gmail.com. No TA and DA will be paid for appearing for the interview. Dr. Shakti Sahi (Principle Investigator)

Advertisement:
www.gbu.ac.in/Recruitment/JRF_Advt_DBTProject_Shakt

Enrichr: a comprehensive gene set enrichment analysis

Jit — Thu, 27 Apr 2017 05:42:09 -0500

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw377

Address of the bookmark: http://amp.pharm.mssm.edu/Enrichr/