WALK- IN –INTERVIEWS

Eligible candidates may appear in Walk-in-Interview on May 23, 2014 at 10 AM for the posts of Research Associates & Senior Research Fellows (SRF) in the following DST/DBT/ICAR funded projects.

1 NPTC Project on Bioinformatics and Comparative Genomics

Research Associate (One)

Rs. 24000/- + 30% HRA for masters degree holder with more than 4 years experience

Essential: Ph D in Plant Molecular Biology & Biotechnology/Genetics 0r Candidates who have already submitted their Ph D thesis in above subjects

Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.

Senior Research Fellow ( UGCCSIR/ DBT/ ICAR Net qualified only): (One)

Rs. 16000/- + 30% HRA and Rs. 18000+30 HRA from 3rd year onwards

Essential:

1. ICAR/ UGCCSIR/DBT Net qualified only

2. M. Sc. (with thesis) in Biotechnology, Life Sciences, Biosciences/ Bioinformatics, Genetics/ Plant Pathology with experience in molecular biology.

Or M.Sc with more than 3 years research experiences

3. B.Sc. Agriculture or Biology

Desirable:
1. M. Sc. with thesis
2. Experience in molecular biology, plant tissue culture
3. Bioinformatics knowledge is important

2 DST JC Bose National Fellowship

Research Associate (Bioinformatics) : One

Rs.22000/- + 30% HRA for 1 & 2nd Yr., Rs. 23000+ 30% HRA for 3rd year and Rs. 24000+30% HRA for 4th &5th yr

Essential: M Ph D in Plant Molecular Biology & Biotechnology/Genetics

Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.

Age limit: Max.35 years (Age relaxation of 5 years for SC/ST & women and 3 years for OBC)

The posts are purely temporary in nature and are co-terminus with the project. Initially the offer will be made for one year only and may be further extendable based on performance of the candidate. The interview will be held on May 23 , 2014 at 10:00 AM at NRCPB, LBS Building, Pusa Campus, IARI, New Delhi- 110012. The candidates must bring four copies of biodata (in the prescribed proforma), original certificates, attested photocopies of each of the certificates and an attested copy of recent passport size photograph. No. TA/DA would be given for the appearance in interview. Only the candidates having essential qualification would be entertained for the interviews. Short-listing of candidates based on academic merit and experience will be done in case of large number of applicants.

Advertisement: http://www.nrcpb.org/sites/default/files/Advertisement%20for%20RA%20and%20SRF%20Position.pdf

Study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. Comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.

Following tools are useful for mis sense muation detection ... 

PolyPhen‐2 (PP2)
“Predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations”

MutationTaster‐2 (MT2)
“Evaluation of the disease‐causing potential of DNA sequence alterations”

MutationAssessor (MASS)
“Predicts the functional impact of amino acid substitutions in proteins, such as mutations discovered in cancer or missense polymorphisms”

LRT
“Identify a subset of deleterious mutations that disrupt highly conserved amino acids within protein‐coding sequences, which are likely to be unconditionally deleterious”

SIFT
“Predicts whether an amino acid substitution affects protein function”

GERP++
“Identifies constrained elements in multiple alignments by quantifying substitution deficits. These deficits represent substitutions that would have occurred if the element were neutral DNA, but did not occur because the element has been under functional constraint. We refer to these deficits as “rejected substitutions.” Rejected substitutions are a natural measure of constraint that reflects the strength of past purifying selection on the element”

phyloP
“Compute conservation or acceleration P values based on an alignment and a model of neutral evolution”

FatHMM unweighted (FatHMM‐U)
Predicts “functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants”

FatHMM weighted (FatHMM‐W)
Predicts “functional consequences of both coding variants, that is, nonsynonymous single‐nucleotide variants, and noncoding variants” and its weighting scheme attributes higher tolerance scores to SNVs in proteins, related proteins, or domains that already include a high fraction of pathogenic variantsh

Combined Annotation Dependent Depletion (CADD)
“CADD is a tool for scoring the deleteriousness of single‐nucleotide variants as well as insertion/deletions variants in the human genome”

C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039

##################################################
[Mon May 7 11:29:18 2018] Reduction...
#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]
/usr/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')
test/run1/contigs.fa 163897 245 66377 40.50 221 90.20 94.854 0 97520 59.50 24 9.80

##################################################
[Mon May 7 11:29:29 2018] Estimating parameters of libraries...
Aligning 19504 mates per library...
Insert size statistics Mates orientation stats
FastQ files read length median mean stdev FF FR RF RR
test/5000_1.fq.gz test/5000_2.fq.gz 50 4998 4990.20 721.47 0 4674 0 0
test/600_1.fq.gz test/600_2.fq.gz 100 599 598.63 47.68 0 10000 0 0

##################################################
[Mon May 7 11:29:29 2018] Scaffolding...
iteration 1.1: test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603
19505 pairs. 17302 passed filtering [88.71%]. 1627 in different contigs [8.34%].
1526 pairs. 558 in different contigs [36.57%].
iteration 1.2: test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536
19505 pairs. 17607 passed filtering [90.27%]. 182 in different contigs [0.93%].
1077 pairs. 124 in different contigs [11.51%].
iteration 2.1: test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536
19505 pairs. 15112 passed filtering [77.48%]. 1295 in different contigs [6.64%].
3417 pairs. 396 in different contigs [11.59%].
iteration 2.2: test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
19505 pairs. 15152 passed filtering [77.68%]. 0 in different contigs [0.00%].
3398 pairs. 0 in different contigs [0.00%].

##################################################
[Mon May 7 11:29:34 2018] Gap closing...
iteration 1.1: test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133

##################################################
[Mon May 7 11:29:35 2018] Final reduction...
#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]
[WARNING] Nothing reduced!
test/run1/scaffolds.filled.fa 99390 1 0 0.00 0 0.00 0.000 0 99390 100.00 1 100.00

##################################################
[Mon May 7 11:29:35 2018] Reporting statistics...
#fname contigs bases GC [%] contigs >1kb bases in contigs >1kb N50 N90 Ns longest
test/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603
test/run1/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603
test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603
test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536
test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536
test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
test/run1/_sspace.2.2.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
test/run1/_gapcloser.1.1.fa 1 99390 39.689 1 99390 99390 99390 2 99390
test/run1/scaffolds.filled.fa 1 99390 39.689 1 99390 99390 99390 2 99390
test/run1/scaffolds.reduced.fa 1 99390 39.689 1 99390 99390 99390 2 99390

##################################################
[Mon May 7 11:29:35 2018] Cleaning-up...
#Time elapsed: 0:00:17.376924

The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.

The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".

The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.

Reference:

http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html

http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme

http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.

https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

Address of the bookmark: https://github.com/knausb/vcfR

CPAT - https://github.com/liguowang/cpat, http://lilab.research.bcm.edu/ (web server)

CPC2 - https://github.com/gao-lab/CPC2_standalone, http://cpc2.gao-lab.org/ (web server)

Infernal - http://eddylab.org/infernal/, https://github.com/EddyRivasLab/infernal

NCBI RefSeq - https://www.ncbi.nlm.nih.gov/refseq/

Rfam - http://rfam.xfam.org/, https://docs.rfam.org/en/latest/index.html

SILVA - https://www.arb-silva.de/

RNAmmer - http://www.cbs.dtu.dk/services/RNAmmer/ (web server, standalone download link)