BOL: Related items

Bioinformatics JRF/RA/SRF position at PANJAB UNIVERSITY

Wed, 19 Nov 2014 20:19:49 -0600

CENTRE FOR SYSTEMS BIOLOGY & BIOINFORMATICS
UIEAST, PANJAB UNIVERSITY, CHANDIGARH

Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology & Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of
the project.

Essential Qualification

For Research Fellow:-

M.Sc. in Systems Biology and Bioinformatics / Life Sciences with minimum 55% marks.

Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology & Bioinformatics will also be eligible.

For Program Assistant:-

The candidate must have M.Sc./M.Tech/MCA/PGDCA in Computer Science and must be able to handle LAN, Linex. Preference will be given to the candidate having experience in
System Administration.

Emoluments

For Research Fellow Rs. 12,500/- per month (Fixed)
For Program Assistant Rs. 12,500/- per month (Fixed)

Applications should be reach on or before 19-11-2014 in the office of the undersigned.

Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology & Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid.

http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf

HASLR: a hybrid assembler which uses both second and third generation sequencing reads

BioStar — Mon, 04 May 2020 02:04:03 -0500

HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.

Address of the bookmark: https://github.com/vpc-ccg/haslr

Bioinformatics SUB DIC (DIC)

Fri, 12 Dec 2014 21:14:57 -0600

Project Title BIOINFORMATICS SUB DIC (DIC)

Reference Number IIT/SRIC/R/DIC/2014/314, DATED 28thNovember, 2014

Temporary Position(s)

i) Junior/ Senior Project Officer (1)
ii) Junior Project Assistant (2)

Consolidated Compensation

i) Rs.16,000/- to Rs.18,000/- p.m. (depending on qualification & experience)
ii) Rs.8,000/- to Rs.10,000/- p.m. (depending on qualification & experience)

Coordinator / PI Dr. Sudip K. Ghosh, Dept of Biotechnology.

Department / Centre / School Dept of Biotechnology

Qualifications & Experience

(i) M. Sc in any branch of Life Sciences with experience in Molecular Biology/Genetics/Biochemistry preferably a Post Graduate diploma in Bioinformatics or two years working experience in bioinformatics (Minimum 60% marks starting from matriculation examination).

(ii) B. Sc. /B.A. /B. Com/Diploma in Management or Computer Science. Knowledge in computer software will be preferred (minimum 50% marks starting from matriculation examination).

More Information

Interested eligible persons may apply on plain paper, giving full bio-data along with attested copies of testimonials to the undersigned on or before 11thDecember, 2014.

Sponsor DBT, NEW DELHI

Last Date 11 Dec 2014

Application Fee Demand Draft for Rs.50/- (Not for female candidates) drawn in favour of IIT Kharagpur payable at Kharagpur

Advertisement: www.iitkgp.ac.in/topfiles/sric_job_details.php?serial=2826

mixtureS: a novel tool for bacterial strain reconstruction from reads

BioStar — Fri, 21 Aug 2020 08:23:19 -0500

mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets.

Availability

The source code and tool mixtureS is available at http://www.cs.ucf.edu/˜xiaoman/mixtureS/.

Address of the bookmark: http://www.cs.ucf.edu/~xiaoman/mixtureS/

Internship Program for Bioinformatics / Biotechnology / MBA / MCA (No. Of Vacancy: 5)

Mon, 15 Dec 2014 08:11:02 -0600

ArrayGen is offering an Internship Program for Post graduate Bioinformatics / Biotechnology / MBA / MCA students and professionals. ArrayGen Technologies provide an excellent opportunity to gain research experience and explore if a scientific career is right for you. Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis or marketing or software development. Applications are accepted throughout the year. Accepted students will be notified through email.

HairSplitter: assembling long reads in an unknown number of haplotypes

BioStar — Wed, 07 Dec 2022 00:13:40 -0600

Pros and cons of HairSplitter Limitations of HairSplitter:

Not very fast: it re-polishes the whole assembly

Limited in the number of haplotypes

Strengths of HairSplitter:

Very modular, can be used with any assembler

Naive: makes no assumption on ploidy, parameter-free

Safe: won’t artificially duplicate contigs

HairSplitter splits collapsed assemblies from “draft” assemblies obtained by any means

HairSplitter can recover haplotypes and distinguish repeated elements

Only needs sequencing reads, potentially error-prone

HairSplitter splits collapsed assemblies from “draft” assemblies obtained by any means

HairSplitter can recover haplotypes and distinguish repeated elements

Only needs sequencing reads, potentially error-prone

Not really available yet (github.com/RolandFaure/HairSplitter)

https://hal.archives-ouvertes.fr/hal-03864075/file/RolandFaure_presentation_SeqBIM_2022.pdf

Address of the bookmark: https://hal.archives-ouvertes.fr/hal-03817928/document

irishgrid: Irish Grid Mapping System

Jit — Fri, 26 Dec 2014 07:53:24 -0600

Perl module for creating geographic 10km-square maps using either SVG or PNG (with GD library) output format.

Originally design to map the location of objects in a 10 km map IrishGrid includes:

native support of the Irish Grid System (see http://www.osi.ie/)
optimize for speed (there's as less as possible data to conversion)
customized color functions

https://code.google.com/p/irishgrid/downloads/detail?name=irishgrid.pl

Address of the bookmark: https://code.google.com/p/irishgrid/

Meraculous: De Novo Genome Assembly with Short Paired-End Reads

Jit — Tue, 07 Nov 2017 04:36:10 -0600

We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by ∼280 bp or ∼3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/

Teaching Assistant at SVIMS

Fri, 31 Jul 2015 10:15:16 -0500

Eligible candidates are invited for a walk-in-interview for recruitment of Teaching Assistant in the Department of Bioinformatics on 8.08.2015 at 10 A.M. in the Committee Hall, SVIMS, Tirupati. The candidates have to attend with all original certificates of qualification, experience on the date of interview. The engagement will be made purely on adhoc basis for a period of 6 months and it can be terminated at any time without notice or without assigning any reason thereof. This is purely an adhoc appointment and the candidate will not have any right to claim permanent benefits of any kind.

1. Remuneration : Rs. 12000/- per month (consolidated)

2. Qualification : M.Sc./M.Tech. Bioinformatics (preference will be given to the candidates with BINC / NET / GATE / Bioinformatics DBT-Traineeship / Studentship and teaching experience)

3. Place of work : Department of Bioinformatics, SVIMS, Tirupati

4. No. of Position : One

Terms and conditions:

1. Candidates are required to submit the Biodata, attested copies of relevant certificates in support of their age, educational qualification, experience etc., before the interview committee, SVIMS University, Tirupati.
2. No TA / DA will be paid for attending the interview.
3. Interim enquiries will not be entertained.
4. The maximum age limit for Teaching Assistant is 34 years as on 8th August, 2015.
5. The tenure of will be further extended subject to performance of the incumbent.

Advertisement: http://svimsbic.org/Teaching_Assistant_B.I._2015.pdf

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