BOL: Related items

GMOL: An Interactive Tool for 3D Genome Structure Visualization

Jit — Wed, 21 Mar 2018 12:25:20 -0500

GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.

Address of the bookmark: https://www.nature.com/articles/srep20802

C-DAC launch supercomputing facility "Param Bio Blaze" !!!

Rahul Nayak — Tue, 18 Feb 2014 11:55:14 -0600

The bioinformatics centre at Centre for Development of Advanced Computing (C-DAC) completed 10 years, this month. Established in 2004, the centre has been widely used by numerous researchers across the globe and has an ultimate aim of making personalised drugs depending on the composition of a human body.

When biological data is processed using computer science, statistics, mathematics and engineering, it constitutes bioinformatics. The technological advancements are bringing new dimensions to the understanding of molecular basis of living organisms. There is immense data generated due to computing, but storage and analysis of this data is becoming a challenge, therefore there is an urgent need of supercomputers.

The C-DAC will launch Param Bio Blaze, a supercomputing facility, to address the challenges in bioinformatics on Tuesday at a three-day symposium, titled: 'Accelerating biology: Computing life'. The supercomputing facility will be inaugurated on Tuesday by Ramakrishna Ramaswamy, vice-chancellor, Central University of Hyderabad at the Yashada. The new C-DAC's facility will have a capacity of 10 teraflop and will be able to analyse human cells and its functions.

Param Bio Blaze will help have a larger storage space and better computing facility for the bioinformatics sector. The facility will help capture the movement of molecules and also interaction between two molecules and the effects.

Applications of Param BioBlaze

- Collaboration with National Centre for Cell Science for research on Malaria and understanding how the disease spreads

- Collaborative work with Tata Memorial hospital on breast cancer and find out the difference between normal tissues and tissues from breast cancer patients

- Designing anti-cancer molecules, a collaborative research with the University of Pune

Reference:

Times of India

Image:datacenterjournal.com

ComparativeGenomics Exercise2

Neel — Wed, 22 Aug 2018 22:10:56 -0500

COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP @ cbs.dtu.dk

Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf

Atlas of ancient inter-ethnic group !!!

Jit — Fri, 14 Feb 2014 13:16:20 -0600

Now a dayz, almost 3% of the world's population lived outside their country of origin. These migration is increasingly being perceived as a force that can contribute to development, and an integral aspect of the global development process. While migrants make important contributions to the economic prosperity of their host countries, the flow of financial, technological, social and human capital back to their countries of origin also is having a significant impact on poverty reduction and economic development.

However, the ancient invasions and migrations to slavery and trade, history is embroidered with events that led to interactions between previously separate populations. Early humans migrated due to many factors such as changing climate and landscape and inadequate food supply. Historical migration of human populations begins with the movement of Homo erectus out of Africa across Eurasia about a million years ago. Homo sapiens appear to have occupied all of Africa about 150,000 years ago, moved out of Africa 70,000 years ago, and had spread across Australia, Asia and Europe by 40,000 years BC. Indo-Aryan migration from the Indus Valley to the plain of the River Ganges in Northern India is presumed to have taken place in the Middle to Late Bronze Age, contemporary to the Late Harappan phase in India (ca. 1700 to 1300 BC). From 180 BC, a series of invasions from Central Asia followed, including those led by the Indo-Greeks, Indo-Scythians, Indo-Parthians and Kushans in the northwestern Indian subcontinent.

Using the recent advance technologies researchers have created a historical atlas of instances of such mixing. They use a sophisticated statistical method for making inferences about human history and infer populations interbredings ( happen over the past 4,000 years) with an ease.

The study published the findings and presented with an interactive map. http://admixturemap.paintmychromosomes.com/

These sort of genomic study have some limilation. It is hard to precisely define sources of mixing when it occurred between genetically similar groups, and scenarios involving multiple waves of mixing over time or between multiple groups can be difficult to tease apart. But it is believed that larger sample sizes will improve resolution. These high resolution will provide a deeper understanding of human history.

Reference:

http://www.sciencemag.org/content/early/2014/01/28/science.1245938

http://www.ncbi.nlm.nih.gov/pubmed/21390129?dopt=Abstract&holding=npg

http://www.csulb.edu/~kmacd/paper-ethnicity.html

Image: Wikipedia

CHARLES SWANTON LAB

Tue, 11 Dec 2018 08:09:22 -0600

They are using the latest DNA sequencing technology to read the genetic makeup of cancer cells within tumours in ever greater detail, teasing out patterns of evolution (evolutionary rule books), cancer heterogeneity and working out what changes have happened as a tumour evolves. We’re also investigating the processes that cause mutations and accelerate tumour evolution and working out how they might be stopped. And we are running evolutionary clinical trials with immune and targeted therapies to bring the benefits of our work to patients as quickly as possible.

https://www.crick.ac.uk/research/labs/charles-swanton

Computational Biologist Scientist @ Strand Life Sciences

Fri, 14 Mar 2014 11:36:56 -0500

We are looking for a motivated application scientist to help evaluate, compare, and develop next generation sequencing (NGS) data analysis methods. The successful candidate should be able to quickly understand the state-of-art computational biology techniques, prototype them and perform benchmarking studies. The candidate must also be comfortable working with people from different disciplines and be able to present data analysis results in a clear and effective manner. The candidate is also expected to interact with customers as needed, write technical reports and publish new methods and/or data analysis findings in public forums.

Candidate Requirements: A PhD in computer science, computational biology, Bioinformatics, or a related field, along with sufficient programming skills for prototyping. Experience with next generation sequencing data analysis is required. Candidates with MS degree but with relevant work experience can also be considered. The successful candidate must be motivated and capable of working independently as well as in team environment.

Eligible and interested candidates can email your resumes to rohit at strandls dot com

About Strand Life Sciences: Strand was founded in 2000 by computer science and mathematics professors who recognized the need to automate and integrate life science data analysis through an algorithmic and computational approach. Strand’s solutions for life sciences research are robust and easy to use by the most novice user while powerful and configurable for the bioinformatician. Using its award-winning application development platform, AVADIS®, Strand builds innovative products that enable fast and cutting-edge analysis for basic and clinical research, drug discovery and development.

http://www.avadis-ngs.com/careers

Roary: the Pan Genome Pipeline

Jit — Tue, 22 Jan 2019 05:52:07 -0600

Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, something which is computationally infeasible with existing methods, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. To perform this analysis using existing methods would take weeks and hundreds of GB of RAM. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes.

Address of the bookmark: https://sanger-pathogens.github.io/Roary/

gVolante: Completeness Assessment of Genome/Transcriptome Sequences

Jit — Tue, 06 Aug 2019 21:37:56 -0500

gVolante provides an online interface for completeness assessment of user’s original or publicly available sequence datasets as well as for browsing results of completeness assessment performed on publicly available genome and transcriptome assemblies.

Address of the bookmark: https://gvolante.riken.jp/

Postdoc Position in Computational Biology

Fri, 14 Mar 2014 01:38:49 -0500

The Computational Biology Group of Interdisciplinary Center for
Clinical Research (IZKF) Aachen, RWTH Aachen University Hospital,
Aachen, invites applicants for PhD candidate or postdoctoral position
in computational biology in one of the following topics:

1) Statistical machine learning methods for the analysis of medical
epigenomics data.

2) Sequence analysis algorithms for detection of RNA-DNA interactions.

Applicants should hold a M.Sc . or PhD in Computer Science or related
areas. Experience in the analysis of biological sequences, gene
expression and gene regulation is desirable. The candidate should have
solid programming skills (C, Python and/or R) and acquaintance with
Linux. Experience with high performance computing is a plus. The
working language of the group is English.

The position is based on the German TV-L 13 salary scale, including
all German social benefits (health insurance and pension scheme). The
expected starting date is September 2014. Interested candidates should
send a CV, statement of research interests and the names of three
references to jobs@costalab.org.

More at http://costalab.org/wp/phd-and-postdoc-position-in-computational-biology/

Synteny and Rearrangement Identifier (SyRI)

Jit — Tue, 05 May 2020 10:37:10 -0500

SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.

Address of the bookmark: https://schneebergerlab.github.io/syri/