BOL: Related items

Important Journals, Blogs and Forums for Bioinformaticians

Jit — Wed, 08 Feb 2017 09:15:31 -0600

Journals. Most journals have RSS feeds for their current updates.

Blogs. Some of these blogs are very relevant to bioinfo jobs. Others are more personal interest.

The OpenHelix Blog
Ensembl blog
Galaxy News
Blue Collar Bioinformatics
Homologus
Golden Helix - our 2 SNPs
Genomics Law Report
R-bloggers (aggregates feeds from >350 blogs about R)
Genomes Unzipped
Jason Moore's Epistasis Blog
23andMe - the Spitoon

Variance Explained: David Robinson’s blog (Data Scientist at Stack Overflow, works in R and Python).
Global Biodefense: News on pathogens, outbreaks, and preparedness, with periodic posts on genomics and bioinformatics-related developments and funding opportunities.
In between lines of code: Lex Nederbragt’s blog on biology, sequencing, bioinformatics, …
Simply Statistics: A statistics blog by Rafa Irizarry, Roger Peng, and Jeff Leek.
Bits of DNA: Reviews and commentary on computational biology by Lior Pachter (fair warning: dialogue here can get a bit heated!).
Blue Collar Bioinformatics: articles related tool validation and the open source bioinformatics community.
Microbiome Digest – Bik’s Picks: A daily digest of scientific microbiome papers, by Elisabeth Bik, Science Editor at uBiome.
Living in an Ivory Basement: Titus Brown’s blog on metagenomics, open science, testing, reproducibility, and programming.
Enseqlopedia: James Hadfield’s blog on all things NGS.
Epistasis Blog: Jason Moore’s computational biology blog.
RStudio Blog: announcements about new RStudio functionality, updates about the tidyverse, and more.
nextgenseek.com: Next-Gen Sequencing Blog covering new developments in NGS data & analysis.
RNA-Seq Blog: Transcriptome Research & Industry News.
The Allium: We all need a little humor in our lives. Like The Onion, but for science.

Forums.

JRF Bioinformatics job vacancies in Tezpur University

Tue, 14 Feb 2017 16:40:26 -0600

Memo No. DoRD/CSE/SSS/20-295/112-A Date: 01/02/2017

Project Title : Integrating genome scale metabolic analysis of model plant pathogen Ralstonia solanacearum with RNAseq and fluxomics

Essential qualification : M.Tech. in CSE/IT (With specialization in Computational Biology/Bioinformatics) or M.Sc. in Bioinformatics/Biosciences/Molecular Biology Biotechnology preferably with NET/GATE/BET. Candidates should have minimum 55 % mark both in 10th and 10+2 Science examinations and mathematics at 10+2 Science. Desirable: Preference will be given to the candidates having experience in computational analysis of genome sequences or similar projects.

No. of Post : 01

Remuneration : Rs. 25,000/- for the 1st two years and Rs. 28,000/- for the 3rd year for SRF and applicable to the candidate having post graduate degree in Basic Science with NET/GATE/BET qualification or post graduate degree in professional course. Rs. 12,000/- for the 1st two years and Rs. 14,000/- for the 3 rd year for SRF,

Age : 28 years

Duration : Three (03) years or till completion of the project or until further order, whichever is earlier.

Hiring Process : Walk - In
Job Role: Research/JRF/SRF

Walk-in-interview will be held on 17th February, 2017, 11.15 a.m. at the office of the Head, Department of Computer Science and Engineering, Tezpur University.

Interested candidates may appear before the interview board with original documents from 10th standard onwards and photocopies of mark sheets, certificates, testimonials, caste certificate (if applicable), experience certificate certificates of NET/GATE/BET or similar examination qualifications, any other testimonials and a copy of recent curriculum vitae (CV) on the day of interview.

More at http://www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-SSS-20-295-112-A.pdf

BRIG

Jit — Thu, 16 Feb 2017 13:14:25 -0600

BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at:http://sourceforge.net/projects/brig

If you have any questions or comments, post them on one of the trackers on BRIG’s SourceForge page:http://sourceforge.net/tracker/?group_id=328245.

Features:

Images show similarity between a central reference sequence and other sequences as concentric rings.
BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.
Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.
Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.
BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously

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

bedtools

Jit — Fri, 24 Feb 2017 04:50:44 -0600

Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one tointersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.

bedtools is developed in the Quinlan laboratory at the University of Utah and benefits from fantastic contributions made by scientists worldwide.

Address of the bookmark: http://bedtools.readthedocs.io/en/latest/index.html

FinisherSC: a repeat-aware and scalable tool for upgrading de novo assembly using long reads

Jit — Mon, 27 Feb 2017 09:49:45 -0600

FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance.

Address of the bookmark: http://kakitone.github.io/finishingTool/

OrthoANI: An improved algorithm and software for calculating average nucleotide identity

Abhimanyu Singh — Wed, 12 Dec 2018 08:36:08 -0600

OAT uses OrthoANI to measure the overall similarity between two genome sequences. ANI and OrthoANI are comparable algorithms: they share the same species demarcation cut-off at 95~96% and large comparison studies have demonstrated both algorithms to produce near identical reciprocal similarities. Details of the OrthoANI algorithm is given in (Lee et al. 2015). OAT employs an easy-to-follow Graphical User Interface that allow researchers to calculate OrthoANI values between genomes of interest without unfamiliar Command Line Environments. Moreover, the OAT_cmd command-line software can be integrated into preexisting bioinformatics pipelines.

Address of the bookmark: https://www.ezbiocloud.net/tools/orthoani

Bioinformatics walk-in-interview at Tezpur University

Thu, 02 Mar 2017 04:24:46 -0600

A walk-in-interview will be held on 09 March, 2017, 11.15 a.m. at the office of the Head, Department of Computer Science and Engineering, Tezpur University for one (01) temporary position of Junior Research Fellow (JRF) in the DBT, Govt. of India sponsored project entitled “Integrating genome scale metabolic analysis of model plant pathogen Ralstonia solanacearum with RNAseq and fluxomics” under Dr. Siddhartha Sankar Satapathy (ssankar@tezu.ernet.in), Associate Professor, Department of Computer Science and Engineering, Tezpur University.

Interested candidates may appear before the interview board with original documents from 10th standard onwards and photocopies of mark sheets, certificates, testimonials, caste certificate (if applicable), experience certificate certificates of NET/GATE/BET or similar examination qualifications, any other testimonials and a copy of recent curriculum vitae (CV) on the day of interview.

Essential qualification: M.Tech. in CSE/IT (With specialization in Computational Biology/Bioinformatics) or M.Sc. in Bioinformatics/Biosciences/Molecular Biology Biotechnology preferably with NET/GATE/BET.

Candidates should have minimum 55 % mark both in 10th and 10+2 Science examinations and mathematics at 10+2 Science.

Desirable: Preference will be given to the candidates having experience in computational analysis of genome sequences or similar projects.

Remuneration: Rs. 25,000/- (Rupees twenty five thousand) only + HRA as admissible per month for the 1st two years and Rs. 28,000/- (Rupees twenty eight thousand) only + HRA as admissible per month for the 3rd year for SRF and applicable to the candidate having post graduate degree in Basic Science with NET/GATE/BET qualification or post graduate degree in professional course. Rs. 12,000/- (Rupees twelve thousand) only + HRA as admissible per month for the 1st two years and Rs. 14,000/- (Rupees fourteen thousand) only + HRA as admissible per month for the 3 rd year for SRF, for the candidate without NET/GATE/BET qualification. HRA will not be provided if campus accommodation is availed.

Age: Candidate shall not be more than 28 years of age on the date of interview. Upper age limit may be relaxed up to 5 years in the case of candidate belonging to SC/ST/ OBC/Women/Differently abled.

Duration: Three (03) years or till completion of the project or until further order, whichever is earlier.

N.B. No TA/DA will be paid to the candidates for attending the interview. For further details please contact: Dr. S. S. Satapathy Associate Professor Department of Computer Science and Engineering Tezpur University, Napaam-784028 Email: ssankar@tezu.ernet.in Contact no.: +91-9435979648

More Info: www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-SSS-20-295-188-A.pdf

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

MetaBAT: An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Jit — Mon, 06 Mar 2017 03:44:34 -0600

MetaBAT, An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Here we developed an automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency. Tested on both synthetic and real metagenome datasets, MetaBAT outperforms alternative methods in both accuracy and computational efficiency. Applying MetaBAT to an assembly from 1,704 human gut samples formed 1,634 genome bins (>200kb) in 3 hours, where 621 genome bins are >50% complete with <5% contamination from other species. Further analysis shows that the quality of these genome bins approaches manually curated genomes.

Address of the bookmark: https://bitbucket.org/berkeleylab/metabat

HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning

Abhimanyu Singh — Tue, 01 Jan 2019 12:01:00 -0600

HECIL—Hybrid Error Correction with Iterative Learning—a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments.

HECIL’s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.

Address of the bookmark: https://github.com/NDBL/HECIL