Salary: £27,854 - £29,541, with progression to £36,298

You will perform cutting edge computational biology within the Faculty of Medical Sciences, with a particular focus on the Northern Institute for Cancer Research (NICR), and contribute to the delivery of Faculty wide programmes of training, analytical services and skill transfer between Faculty Institutes.

You will have a relevant first degree or equivalent qualifications and/or experience in a relevant scientific/technical role, together with previous specialist experience at a senior level in bioinformatics. A PhD is desirable.

This position is part of the Bioinformatics Support Unit but physically located for the majority of the time in the NICR buildings.

Tenable for three years.

Informal enquiries to unit head Dr Simon Cockell: 0191 222 7253; simon.cockell@ncl.ac.uk

For more information visit @ https://www15.i-grasp.com/fe/tpl_newcastle02.asp?s=4A515F4E5A565B1A&jobid=50667,2552984041&key=70203469&c=725434237887&pagestamp=sepghtjhowdqpsxuyn

You can also find several other jobs @http://bsu.ncl.ac.uk/support/recruitment/

Address of the bookmark: https://github.com/PapenfussLab/gridss

Functioning of efflux systems in Gram-negative bacteria
Determinants of the compound-efflux system interactions
Action of inhibitors on efflux systems
Structural and dynamical features of the efflux systems

TatA
Assembly of the TatA system
Study of the dynamical features of the charge zipper

Methods
Setup of a kinetic Monte Carlo (KMC) scheme to study the flux of antibiotics through porins and efflux systems
Setup of protocol to integrate MD results in a ligand-based approach

Viral inhibitors
Interactions of selected compounds with RNA-dependent RNA polymerases (RdRps) of HCV and BVDV
Assessment of the role of mutations in RdRps
Antimicrobial peptides

Interactions of antimicrobial peptides with membranes: structure and dynamics
Interactions between antimicrobial peptides in the presence of different membranes
Protein-protein interactions
Effects of mutations

Lab Page
http://www.dsf.unica.it/~paolo/Site/Home.html

The MMseqs2 user guide is available as Github Wiki or as PDF file (Thanks to pandoc!)

Please cite: Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017).

Address of the bookmark: https://github.com/soedinglab/MMseqs2

Genome Annotation and Functional Genomics

Bergman Lab is actively engaged in the development and application of computational methods to improve the annotation of functional biological features in genome sequences. Bergman Lab work focuses on improving annotation of non-protein-coding regions of the genome including conserved noncoding sequences (CNSs), cis-regulatory modules (CRMs), transcription factor binding sites (TFBSs), transposable elements (TEs) and noncoding RNA (ncRNA) genes. Current projects include improving the (i) annotation of TEs in the fly and yeast genomes, (ii) annotation of CRMs and TFBSs in the fly genome, and (iii) analysis of transposon knockout collections in flies. Research in this area is supported by the EC FP7 programme.

Genome and Molecular Evolution
Text and Data Mining

More @ http://bergmanlab.smith.man.ac.uk/

Arlequin: http://cmpg.unibe.ch/software/arlequin3/

BEAGLE: http://faculty.washington.edu/browning/beagle/beagle.html

fastPHASE: http://stephenslab.uchicago.edu/software.html

GENEHUNTER: http://linkage.rockefeller.edu/soft/gh/

The Genome Analysis Toolkit:

http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit

IMPUTE2: https://mathgen.stats.ox.ac.uk/impute/impute_v2.html

MACH: http://www.sph.umich.edu/csg/abecasis/MACH/

MERLIN: http://www.sph.umich.edu/csg/abecasis/Merlin/

PHASE: http://stephenslab.uchicago.edu/software.html

PL-EM: http://www.people.fas.harvard.edu/~junliu/plem/

“Read-backed phasing” algorithm: http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm

SHAPE-IT: http://www.griv.org/shapeit/

Nature Biotechnology spoke with Altschul and several other originators of computational biology software programs widely used today (Table 1). The conversations explored what makes certain software tools successful, the unique challenges of developing them for biological research and how the field of computational biology, as a whole, can move research agendas forward. What follows is an edited compilation of interviews.

Detail @ http://www.nature.com/nbt/journal/v31/n10/full/nbt.2721.html

News Source @ Nature

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”

2013 Oct Advertisement from Indian Statistical Institute

Post: Network Analysis

No. of Positions: 01

Educational Qualifications:

Candidate should have passed BE/B.Tech Or Equivalent in Computer Science / Electrical Engineering / Electronics / Information Technology / Bioinformatics / Biotechnology with throughout first Class
Experience:

(details of experience required)
Pay Scale: INR Rs.16000-20000/-P.M.

Walk-In-Interview : 22 Oct 2013 at 10:30 AM

Download Official Notification:
http://www.isical.ac.in/JobApplicationFiles/MIU_0310201311433700.pdf

##################################################
[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