BOL: Related items

4DGenome

Jitendra Narayan — Mon, 04 Jul 2016 00:44:55 -0500

Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.

All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.

Address of the bookmark: http://4dgenome.research.chop.edu/

Sequence - Evolution - Function; Computational Approaches in Comparative Genomics

Jit — Sun, 06 Aug 2017 06:58:12 -0500

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/books/NBK20260/

Computational resources for TE discovery and TE detection

Abhimanyu Singh — Mon, 12 Feb 2018 10:29:18 -0600

Transposable Elements (TEs) to genome structure and evolution as well as their impact on genome sequencing, assembly, annotation and alignment has generated increasing interest in developing new methods for their computational analysis.

Following are the list of resource and location for TE discovery and TE detection:

BLASTER suite http://urgi.versailles.inra.fr/development/blaster/

Censor http://www.girinst.org/censor/download.php

find_ltr http://darwin.informatics.indiana.edu/cgi-bin/evolution/ltr.pl

FINDMITE http://jaketu.biochem.vt.edu/dl_software.htm

HMMER http://hmmer.janelia.org/

LTR_FINDER http://tlife.fudan.edu.cn/ltr_finder/

LTR_STRUC http://www.genetics.uga.edu/retrolab/data/LTR_Struc.html

LTR_MINER http://genomebiology.com/2004/5/10/R79/suppl/s7

LTR_par http://www.eecs.wsu.edu/~ananth/software.htm

MAK http://wesslercluster.plantbio.uga.edu/mak06.html

MaskerAid http://blast.wustl.edu/maskeraid/

mer-engine http://mer-engine.cshl.edu/mer-home.php

mreps http://bioinfo.lifl.fr/mreps/

PILER http://www.drive5.com/piler/

PLOTREP http://repeats.abc.hu/cgi-bin/plotrep.pl

RepBase http://www.girinst.org/

RepeatFinder http://cbcb.umd.edu/software/RepeatFinder/

RepeatGluer http://nbcr.sdsc.edu/euler/intro_tmp.htm

RepeatMasker http://www.repeatmasker.org/

RepeatRunner http://www.yandell-lab.org/repeat_runner/index.html

RepeatScout http://repeatscout.bioprojects.org/

repeat-match http://mummer.sourceforge.net/

REPuter http://www.genomes.de/

RetroMap http://www.burchsite.com/bioi/RetroMapHome.html

SMaRTFinder http://bioinf.dimi.uniud.it/software/software/smartfinder

Tandem Repeats Finder http://tandem.bu.edu/trf/trf.html

Transposon Cluster Finder http://www.mssm.edu/labs/warbup01/paper/files.html

TE nest http://www.plantgdb.org/prj/TE_nest/TE_nest.html

TRANSPO http://alggen.lsi.upc.es/recerca/search/transpo/transpo.html

TSDfinder http://www.ncbi.nlm.nih.gov/CBBresearch/Landsman/TSDfinder/

Tu Lab TE tools http://jaketu.biochem.vt.edu/dl_software.htm

WU-BLAST http://blast.wustl.edu

PLANT COMPUTATIONAL GENOMICS LAB – JILL WEGRZYN

Thu, 20 Aug 2020 19:49:12 -0500

Our research focuses on the computational analysis of genomic and transcriptomic sequences from non-model plant species. We do this by developing approaches to examine gene finding, gene expression, transcriptome assembly, and conserved element identification, through machine learning and computational statistics. We use these novel methods to address questions related to genome biology and population genomics.

We also develop web-based applications that integrate data across domains to facilitate the forest geneticist or ecologist’s ability to analyze, share, and visualize their data. Such integration requires the implementation of semantic technologies and ontologies to connect genotype, phenotype, and environmental data.

http://plantcompgenomics.com/

One-year position for a bioinformatician / computational biologist in population genetics

Fri, 05 Feb 2021 11:19:02 -0600

The successful candidate will work as support staff mainly in the development, application and maintenance of pipelines for handling large omics datasets (including whole-genome sequences, high-density genotypes and mRNA sequences). These pipelines cover pre-processing of data, statistical analyses and genome bioinformatics. The postholder will also provide support in producing high-level graphic representations of
these data and of results from their analysis. Our team is part of UMR
7268 ADES research unit (Anthropologie bio-culturelle, Droit, Ethique
et Sant=E9), located at the Timone Faculty of Medicine (Aix-Marseille
University, 13005 Marseille).

JOB QUALIFICATION
- PhD/Engineer/MSc in bioinformatics, biostatistics, genetics/genomics
or any related field.
- Advanced knowledge of Bash/Perl scripting and job management on a Unix
HPC and in at least one basic language for data
manipulation/statistics (such as R/Python/Matlab) are required.
- Knowledge of at least one programming language (e.g. C), experience
processing -omics data or skills in advanced graphical representation
of data would be a plus.

DURATION
1 year, not extensible

SALARY
Gross salary is commensurate with experience and grade (MSc from
1,882=80/month and PhD/equivalent from 2,099=80/month).

APPLICATIONS/OPENING
Please send a motivation letter, a CV and the names of two referees to
pierre.faux@univ-amu.fr. The expected starting date is April 1st, 2021;
the job offer will however remain opened until the position is filled.

Pierre Faux

Troyanskaya Lab

Tue, 04 Feb 2020 06:40:36 -0600

The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.

https://function.princeton.edu/

RNA-Seq differential expression work flow using DESeq2

BioStar — Mon, 23 Aug 2021 10:57:14 -0500

One of the aim of RNAseq data analysis is the detection of differentially expressed genes. The package DESeq2 provides methods to test for differential expression analysis.

Address of the bookmark: http://www.sthda.com/english/wiki/rna-seq-differential-expression-work-flow-using-deseq2

Awesome bioinformatics pipelines !

Jitendra Prajapati — Wed, 30 Mar 2016 21:50:41 -0500

A curated list of awesome pipeline toolkits ...

https://github.com/pditommaso/awesome-pipeline

Address of the bookmark: https://github.com/pditommaso/awesome-pipeline

Luigi: a Python package that helps you build complex pipelines of batch jobs.

Neel — Thu, 24 Jun 2021 05:43:31 -0500

Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more.

Run pip install luigi to install the latest stable version from PyPI. Documentation for the latest release is hosted on readthedocs.

Run pip install luigi[toml] to install Luigi with TOML-based configs support.

Address of the bookmark: https://github.com/spotify/luigi

Bioinformatics Scientist – ICMR Computational Genomics Centre

Sat, 26 Dec 2020 10:18:29 -0600

ICMR invites online applications, from Indian Citizens, up to 8th January 2020 till 5:30 PM to fill up the following post to be filled purely on a temporary basis under “ICMR Computational Genomics Centre” under Dr. Harpreet Singh, Head, Division of Biomedical Informatics (BMI), ICMR HQRS, New Delhi 110029.
The Terms & Conditions for the post are as follows:

a) Scientist-B – UR (2 posts-Bioinformatics) on consolidated salary of Rs.48,000/- pm + HRA

b) Scientist C – UR (1 post -Bioinformatics) on consolidated salary of Rs. 51,000 pm+ HRA

c) Scientist B- UR (2 post-Statistics) on a consolidated salary of Rs.48,000/- pm +HRA

d) Computer Programmer 1 post UR & 1 post SC on a consolidated salary of Rs. 32,500/- pm

e) Research Assistant -UR 1 post on a consolidated salary of Rs. 31,000/- pm

More at https://projectjobs.icmr.org.in/sccbioinformatics/uploads/recruitment/Adv_BMI_24122020.pdf