BOL: Related items

Sundar Lab

Mon, 23 Sep 2013 11:10:16 -0500

Area of interest

Understanding DNA-protein interactions, genome engineering
Computational Genomics and Bioinformatics
Secondary metabolite biosynthesis, metabolic engineering

Ongoing Projects:

"Betraying the parasite’s redox system: Studies on spermidine synthase of Leishmania donovani "

"Towards modifying nature's DNA-recognition system"

"Yield enhancement strategies for production of therapeutic compounds by cell and tissue cultures of Tinospora cordifolia (willd.) Miers ex Hook. F. & Thoms"

"Program support for Computational Genomics"

More at http://web.iitd.ac.in/~sundar/

Bioinformatics Training Material !

BioStar — Sat, 18 Mar 2023 11:26:18 -0500

Glittr is a curated list of bioinformatics training material.
All material is:

In a GitHub or GitLab repository
Free to use
Written in markdown or similar

NOTE: This list of courses is selected only based on the above criteria.
There are no checks on quality.

https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

Address of the bookmark: https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc

Sandelin group

Mon, 30 Sep 2013 19:12:58 -0500

Sandelin group have a deep interest in most biology, but focus on gene regulation and the many areas that are connected with this, including transcriptomics, epigenetics and technological and informatics aspects.

The group is both computational and experimental.

We ask biological questions to large datasets made using novel genomics techniques, with the help of computers. One of the strengths in the group are the many connections to high-profile experimental laboratories which supply data to be analyzed.

Lab webpage @ http://people.binf.ku.dk/albin/Sandelin_group_at_the_Bioinformatic_Centre/The_Sandelin_group.html

BioKit: a set of tools dedicated to bioinformatics, data visualisation

Neel — Tue, 18 Jun 2024 02:04:39 -0500

BioKit is a set of tools dedicated to bioinformatics, data visualisation (biokit.viz), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g., biokit.stats). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html

National Training on Bioinformatics Computational Tools for Microbial Research Nov 19 to 30, 2013

Fri, 27 Sep 2013 10:49:34 -0500

Agricultural research in modern scientific arena is being represented by proper integration among various research fields of biological, chemical and physical sciences, because this field encompasses many more complexities of biology in nature. In the era of fast accumulating biological data coming out from the research on many crop plants, live stocks and microbes and the impact of changing climate, habitat and other interrelations on these biological entities, bioinformatics has come forward across the globe to solve the problems of analysis, prediction, storage, management, pattern recognition, submission, retrieval and storage of the data to find out a fruitful outcome. This area is becoming increasingly important in the context of systems biology approach where a holistic approach is required to understand the biology and chemistry of the biological entities and their behavior during environmental interactions to resolve the harmful impact of biotic or abiotic causes on crop plants, animals, fishes, livestock sector, beneficial insects as well as microbes. The National Training program on ‘Computational Tools for Microbial Research” is an initiative for the capacity building of NARS scientists/researchers in this most emerging area and fast developing area of i.e. agricultural bioinformatics.

Contact The Director, National Bureau of Agriculturally Important Microorganisms, Kusmaur, Maunath Bhanjan-275101 (U.P.); Phone: 0547-2530080, Fax: 0547-2530358, e mail: nbaimicar@gmail.com; website: www.nbaim.org.in OR

Dr. Dhananjaya P. Singh, Senior Scientist & CCPI, NABG project, NBAIM, Maunath Bhanjan, 275101; Mob.- 09415291703; e mail - dpsfarm@rediffmail.com, nabg.nbaim@gmail.com

More at http://www.nbaim.org.in/Announc.aspx?cd=36

Does anyone have Nanopore latest updates?

Poonam Mahapatra — Mon, 12 Aug 2013 12:19:29 -0500

There was a lot of buzz about Oxford Nanopore Technologies® is developing the GridION™ system and miniaturised MinION™ device. These are a new generation of electronic molecular analysis system for use in scientific research, personalised medicine, crop science, security/defence and more. The platform technology uses nanopores to analyse single molecules including DNA/RNA and proteins. With a broad patent portfolio, the Oxford Nanopore pipeline includes biological nanopores and solid-state nanopores.

Is this available, or still under trial mode?

https://www.nanoporetech.com/

https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system

EMBL Postdoc position in Bacterial Gene Gain Loss

Thu, 20 Aug 2015 14:09:21 -0500

A post-doctoral fellowship is available in the research groups of Nick Goldman (EBI) and John Welch (Genetics Department, Cambridge University) under the EMBL-EBI / Cambridge Computational Biomedical Postdoctoral Fellowship scheme.

The project is on bacterial gene gain and loss and emerging pathogenicity, and is described in full here: https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015 . The EMBL-EBI / Cambridge Computational Biomedical Postdoctoral (“EBPOD”)

The closing date for applications is 3 September 2015. Nick Goldman EMBL-European Bioinformatics Institute Nick Goldman

More at https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015

A powerful, yet simple, gene set analysis tool for interpreting RNA-seq and NGS results.

Shani — Thu, 30 Oct 2014 09:19:29 -0500

LifeMap Sciences is introducing GeneAnalytics, our new gene set analysis tool, which is applicable for NGS results and differentially expressed gene lists from variable sources. GeneAnalytics provides gene associations with tissues & cells, diseases, pathways, GO terms and compounds.

Our main advantages over other similar tools are:

GeneAnalytics is very simple and intuitive to use.
GeneAnalytics is based on our proprietary databases – GeneCards, MalaCards, PathCards and LifeMap Discovery, each of them integrates information from a very large number of resources.
GeneAnalytics supplies links for extensive background information on each of the matched results.

I invite you to try it out for free at geneanalytics.genecards.org, and would be happy to hear your comments and thoughts on how we can improve.

Yours,

Shani Ben-Ari Fuchs

LifeMap Sciences Team

Mike Ritchie Lab

Wed, 02 Oct 2013 15:25:45 -0500

Mike Ritchie Lab primary research focus is the detection of susceptibility genes for common diseases such as cancer, diabetes, hypertension, and cardiovascular disease, among others. The approaches will involve the development and application of new statistical methods with a focus on the detection of gene-gene interactions associated with human disease.

Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/

Alignment of closely related whole genomes/scaffolds

Rahul Nayak — Fri, 29 Jan 2016 10:37:27 -0600

With the relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.This bookmaks have been created to report new tools for whole genome alignments.

Please report new whole genome alignment tools under comment sections.

Address of the bookmark: http://www.cs.utoronto.ca/~brudno/721.full.pdf