BOL: Related items

DBT – Bioinformatics Industrial Training Programme (BIITP) 2016 – 17

Jit — Wed, 27 Jul 2016 04:09:59 -0500

BIITP is a programme of Department of Biotechnology (DBT), Ministry of Science and Technology, Government of India, managed by Biotech Consortium India Limited (BCIL).The objective of BIITP is to provide an opportunity to bioinformatics students to acquire practical skills and experience by working on projects alongside industry experts as well as to provide an opportunity for the industry to identify potential employees.

DBT Invites online applications from the bioinformatics students and requisitions from biotech/bioinformatics companies.

Biotech Industry :

Biotech/Bioinformatics companies interested to provide hands on industrial training to the students of Bioinformatics under BIITP may apply online. The companies would have no obligation towards any payments to trainees. The companies would be paid bench fee to cover expenses towards training. Trainees would be provided to companies subject to availability.

Attn: Bioinformatics Students

Bioinformatics students interested in training in biotech / bioinformatics companies may apply online. Stipend of Rs. 10,000/- per month will be paid to candidates placed for training. The candidates will be selected for training through an interview.

Eligiblity :

a) B.E /B.Tech./M.Sc./M.Tech./Advanced Post Graduate Diploma in Bioinformatics from an Indian recognized university with minimum 55% marks or equivalent grade at highest degree/diploma completed in the year 2015 or 2016 are only eligible to apply.

b) The Advanced Post Graduate diploma should be of at least one year duration after graduation.

c) Students whose result of last semester/final year is not declared can also apply mentioning their marks upto the semester/year upto which result declared. The final result with original mark sheet(s) of all the semesters/years will have to be produced at the time of interview.

Application Procedure :

The online application form is available below :

Application Form For Students (New User)

Requisition form for companies (New User)

Already registered User Click Here

The following documents are to be sent to Mr. Manoj Gupta, Manager, Biotech Consortium India Limited, 5th floor, Anuvrat Bhawan, 210, Deen Dayal UpadhyayaMarg, New Delhi-110002.

More at http://www.bcil.nic.in/biitp2016-17/index.asp

Bioinformatics Technical Position at CDAC Pune - India

Mon, 01 Aug 2016 03:36:26 -0500

CDAC Pune Recruitment 2016 – Apply Online for Technical Positions: Department of Information Technology under the Ministry of Communications and Information Technology, Government of India, Centre for Development of Advanced Computing (C-DAC), Pune has advertised notification for the recruitment of Technical vacancies for for PwD candidates n direct recruitment basis. Eligible candidates can apply Online from 27-07-2016 at 10.00 AM to 31-08-2016 at 18.00 PM.. Other information like age limit, educational qualification, selection process & how to apply are given below…

CDAC Pune Vacancy Details:
Total No. of Posts: 23

Name of the Post: Technical

Name of the Discipline:
A. Computer Science/ Information Technology and Allied disciplines.

B.Electronics Communications/ Electrical/ Telecommunication/Instrumentation & Control/ Medical Electronics/ Power Electronics/ VLSI & Embedded System and Allied disciplines.

C.Biotechnology/ Bioinformatics/ Health informatics/ Geoinformatics/ Meteorology/ Environmental Science/ Ocean Sciences/Oceanography/Environmental Engineering

1. Visually Impaired: 09 Posts

2. Hearing Impaired: 08 Posts

3. Orthopedically Impaired: 06 Posts

Educational Qualification : Candidates should possess Graduation in relvany discpline with relevant experience.

Selection Process: Candidates will be selected based on applicants performance in interview.

How to Apply: Eligible candidates can apply online through the website www.cdac.in from 27-07-2016 at 10.00 AM to 31-08-2016 at 18.00 PM.

More at http://www.cdac.in/index.aspx?id=current_jobs

Comparison of Short Read De Novo Alignment Algorithms

Rahul Agarwal — Wed, 21 Aug 2013 07:56:01 -0500

Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.

Title: Comparison of Short Read De Novo Alignment Algorithms

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

Research Project at IIT, Madras

Wed, 17 Aug 2016 03:26:06 -0500

Two project positions are available to work on (i) molecular modeling and molecular dynamics simulations and (ii) development of bioinformatics databases and tools at Protein Bioinformatics Lab, Department of Biotechnology, IIT Madras.

Duration : Initially for a period of one year. Extendable based on the performance.

Qualification: (i) MSc in Bioinformatics, Biotechnology, Physics, Biophysics, Biochemistry,Computer Science with NET (UGC/CSIR/GATE/BINC/INSPIRE etc) qualification. (OR) (ii) M. Tech in Bioinformatics, Biotechnology

Additional qualification: Programming skills

Candidates who fulfill the requirements of IIT have the possibility to register for PhD.

Fellowship: Rs.25,000 and HRA.

Applicants are encouraged to send the CV to the coordinator by postal mail and e-mail. The deadline to receive the applications is 31st August 2016. The project coordinator has the discretion to restrict the number of candidates to be called for interview to a reasonable limit on the basis of qualifications and experience higher than the minimum prescribed in the announcement.

Project Co-ordinator:

Dr. M. Michael Gromiha
Department of Biotechnology
Indian Institute of Technology Madras
Chennai 600036
Email: gromiha@iitm.ac.in

coursera genome assembly tutorial

Jit — Sat, 25 Nov 2017 08:57:25 -0600

Solutions to Coursera Genome Sequencing (Bioinformatics II)

Address of the bookmark: https://github.com/iansealy/coursera-assembly

3d-dna: 3D de novo assembly (3D DNA) pipeline

Jit — Thu, 28 Dec 2017 10:09:37 -0600

This code is designed to enable anyone to reproduce the Hs2-HiC and the AaegL4 genomes reported in: Dudchenko et al., De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science, 2017.

Unless otherwise noted, all terminology below is consistent with this paper, and all references to figures and tables in this readme refer to this paper. Specifically, some of the terminology used below is outlined in Figure S2. The assembly procedure is described in detail in the Supporting Online Materials, specifically in the section labelled “Pipeline description”.

In addition, the pipeline uses tools and methods from Juicer (Durand & Shamim et al., Cell Systems, 2016) and Juicebox (Durand & Robinson et al., Cell Systems, 2016), as well as additional dependencies noted below.

Feel free to post your questions and comments at: http://www.aidenlab.org/forum.html

http://aidenlab.org/documentation.html

Address of the bookmark: https://github.com/theaidenlab/3d-dna

SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)

Mon, 19 Sep 2016 05:43:38 -0500

SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)
Title : “Transcriptome and small RNA diversity analysis of developing seed contrasting rice varieties”
Qualification : Candidates having M.Sc./M.Tech. degree or equivalent (with minimum 60% marks) in Bioinformatics with a minimum of two years of post M.Sc./M.Tech research experience are eligible to apply.
No. of Post : 01
How to apply
Application should reach to Dr. Pinky Agarwal, Staff Scientist, National Institute of Plant Genome Research (NIPGR) Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 30/09/2016

More at http://www.nipgr.res.in/careers/vacancies_latest.php#

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Rahul Nayak — Tue, 05 Jun 2018 09:57:11 -0500

PERGA - Paired End Reads Guided Assembler PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds. Instead of using single-end reads to construct contig, PERGA uses paired-end reads and different read overlap sizes from O ≥ Omax to Omin to resolve the gaps and branches. Moreover, by constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. PERGA will try to extend the contigs by all feasible nucleotides and determine if these multiple extensions due to sequencing errors or repeats by using looking ahead technology, and it also try to separate the different repeats of nearby genomic regions to make the assembly result more longer and accurate. The simulated E.coli paired-end reads data are generated using GemSim (KE McElroy, F Luciani, T Thomas. Gemsim: General, Error-Model Based Simulator of Next-Generation Sequencing Data. BMC Genomics 2012, 13:74), with coverage 50x, 60x, 100x, read lengths 100-bp, and can be downloaded from https://github.com/zhuxiao/data_PERGA.

Address of the bookmark: https://github.com/hitbio/PERGA

ASplice: a scalable and memory-efficient algorithm for de novo transcriptome assembly

Rahul Nayak — Tue, 03 Jul 2018 04:09:46 -0500

With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from high-throughput sequencing data, they are very memory-intensive, limiting their applications to small data sets with few libraries. Texas A&M University researchers develop a transcriptome assembly algorithm that recovers alternatively spliced isoforms and expression levels while utilizing as many RNA-Seq libraries as possible that contain hundreds of gigabases of data. New techniques are developed so that computations can be performed on a computing cluster with moderate amount of physical memory. Availability – A software program that implements the algorithm is available at: http://faculty.cse.tamu.edu/shsze/asplice. Sze SH, Pimsler ML, Tomberlin JK, Jones CD, Tarone AM. (2017) A scalable and memory-efficient algorithm for de novo transcriptome assembly of non-model organisms. BMC Genomics 18(Suppl 4):387.

Address of the bookmark: http://faculty.cse.tamu.edu/shsze/asplice/

MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

Jit — Wed, 14 Nov 2018 04:50:27 -0600

MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct de Bruijn graph (SdBG) to achieve low memory assembly. MEGAHIT can optionally utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.

https://academic.oup.com/bioinformatics/article/31/10/1674/177884

Address of the bookmark: https://github.com/voutcn/megahit