BOL: Related items

transrate: Understanding your transcriptome assembly

Neel — Fri, 13 Jul 2018 07:49:26 -0500

Transrate is software for de-novo transcriptome assembly quality analysis. It examines your assembly in detail and compares it to experimental evidence such as the sequencing reads, reporting quality scores for contigs and assemblies. This allows you to choose between assemblers and parameters, filter out the bad contigs from an assembly, and help decide when to stop trying to improve the assembly.

Address of the bookmark: http://hibberdlab.com/transrate/index.html

Postdoctoral Research Position in Bioinformatics in Milan

Thu, 20 Apr 2017 12:53:12 -0500

The lab of Immunobiology of Neurological Disorders has a main interest in the biological processes associated with multiple sclerosis, an inflammatory disorder of the central nervous system. The projects of interest for this application involve research on translational bioinformatics in complex human neurological disorders.

You have a PhD in Computational Science, Bioinformatics, or equivalent, and expertise in analysis and modeling of human RNA-seq data, statistics, data mining and machine learning. Excellent communication skills in English (written and oral) is a must. Flexibility and willingness to work across multiple projects and technologies in a rapidly evolving scientific context is required.
Salary will depend on qualification and experience. Starting date: immediate.

Interested candidates should send to farina.cinthia@hsr.it:

1. CV (please show evidences of relevant titles, projects, courses, references, etc.)
2. One page with a list of research topics (i.e. ongoing projects)
3. earliest availability

4. 2-3 contact names

Bioinformatics walk-in-interview at Tezpur University

Thu, 02 Mar 2017 04:24:46 -0600

A walk-in-interview will be held on 09 March, 2017, 11.15 a.m. at the office of the Head, Department of Computer Science and Engineering, Tezpur University for one (01) temporary position of Junior Research Fellow (JRF) in the DBT, Govt. of India sponsored project entitled “Integrating genome scale metabolic analysis of model plant pathogen Ralstonia solanacearum with RNAseq and fluxomics” under Dr. Siddhartha Sankar Satapathy (ssankar@tezu.ernet.in), Associate Professor, Department of Computer Science and Engineering, Tezpur University.

Interested candidates may appear before the interview board with original documents from 10th standard onwards and photocopies of mark sheets, certificates, testimonials, caste certificate (if applicable), experience certificate certificates of NET/GATE/BET or similar examination qualifications, any other testimonials and a copy of recent curriculum vitae (CV) on the day of interview.

Essential qualification: M.Tech. in CSE/IT (With specialization in Computational Biology/Bioinformatics) or M.Sc. in Bioinformatics/Biosciences/Molecular Biology Biotechnology preferably with NET/GATE/BET.

Candidates should have minimum 55 % mark both in 10th and 10+2 Science examinations and mathematics at 10+2 Science.

Desirable: Preference will be given to the candidates having experience in computational analysis of genome sequences or similar projects.

Remuneration: Rs. 25,000/- (Rupees twenty five thousand) only + HRA as admissible per month for the 1st two years and Rs. 28,000/- (Rupees twenty eight thousand) only + HRA as admissible per month for the 3rd year for SRF and applicable to the candidate having post graduate degree in Basic Science with NET/GATE/BET qualification or post graduate degree in professional course. Rs. 12,000/- (Rupees twelve thousand) only + HRA as admissible per month for the 1st two years and Rs. 14,000/- (Rupees fourteen thousand) only + HRA as admissible per month for the 3 rd year for SRF, for the candidate without NET/GATE/BET qualification. HRA will not be provided if campus accommodation is availed.

Age: Candidate shall not be more than 28 years of age on the date of interview. Upper age limit may be relaxed up to 5 years in the case of candidate belonging to SC/ST/ OBC/Women/Differently abled.

Duration: Three (03) years or till completion of the project or until further order, whichever is earlier.

N.B. No TA/DA will be paid to the candidates for attending the interview. For further details please contact: Dr. S. S. Satapathy Associate Professor Department of Computer Science and Engineering Tezpur University, Napaam-784028 Email: ssankar@tezu.ernet.in Contact no.: +91-9435979648

More Info: www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-SSS-20-295-188-A.pdf

ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data

BioStar — Thu, 20 Dec 2018 12:03:32 -0600

The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps: prune, partition, rescue, optimize and build.

Address of the bookmark: https://github.com/tangerzhang/ALLHiC/wiki

SvABA: Genome-wide detection of structural variants and indels by local assembly

Abhimanyu Singh — Mon, 21 Jan 2019 17:58:56 -0600

SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of SGA (String Graph Assembler) by Jared Simpson, and BWA-MEM by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using VariantBam rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.

Address of the bookmark: https://github.com/walaj/svaba

Lifemap

Jit — Mon, 10 Apr 2017 05:42:37 -0500

Lifemap is an interactive tool to explore the WHOLE NCBI TAXONOMY. The concept used in Lifemap is similar to the one used in cartography with tools like Google Maps© or Open Street Maps: exploring is done by zooming and panning.

The current tree contains ALL species present in NCBI taxonomy as of October 18th, 2016: 1,135,169 species including 10,545 Archaea, 418,777 Bacteria and 705,847 Eukaryotes. The Lifemap tree is updated every two weeks.

All the nodes in the tree are clickable. This displays various information and options:

The species name (and the associated common name if there is one)
The rank (kingdom, family, class, species...)
Ability to go to the corresponding node/species on NCBI web site (displayed in a new window)
Possibility to download the corresponding subtree in newick extended format
Possibilty to get the whole lineage from the current node/tip to the root of the tree.

Address of the bookmark: http://lifemap-ncbi.univ-lyon1.fr/

RA Bioinformatics at JNU, New Delhi, INDIA

Thu, 27 Apr 2017 03:29:58 -0500

School of Computational & Integrative Sciences
Jawaharlal Nehru University
New Delhi-110067, INDIA

Date: April 24th. 2017 Last Date: May 6th 2017
PROJECT ID: 632

The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project jointly running with IIIT-Hyderabad & JNU, entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067.
NB: For all the posts, preference will be given to candidates with a good knowledge of Python and/or R in UNIX platform , knowledge of JAVA will also get a special consideration.

1. RA / Research Associate (Metabolic engineering/Computational Biologist)

Salary: Rs. 36000/- + HRA

Vacancy: 1

Essential Qualifications: PhD in Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/Analysis of Network Biology/Chemoinformatics/Computational Biology related Software development. Published paper in the field is a must to prove the experience. Special consideration will be given if have experience in Industry, teaching & product development.

Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , collaborating with industry , preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.

2. Project SRF (Network model building/Systems biology integration)

Salary*: Rs.18000/- + HRA

Vacancy: 1

Essential Qualifications: M.Tech in Computational Biology with project experience or Masters / B.Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Mathematical Model building using Computational Biology tools & related Database / Network analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal whereas for M.Tech, the degree obtained in computational biology is a must.

Desired Skills: Will be expected to manage ongoing research activities in LIMS, interact with LIMS group, build network model using data compiled by experimentalist, prepare and file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.

More at http://www.jnu.ac.in/Career/currentjobs.htm

NextDenovo: string graph-based de novo assembler for TGS long reads

Jit — Sun, 05 Jan 2020 04:08:29 -0600

NextDenovo is a string graph-based de novo assembler for TGS long reads. It uses a "correct-then-assemble" strategy similar to canu, but requires significantly less computing resources and storages. After assembly, the per-base error rate is about 97-98%, to further improve single base accuracy, please use NextPolish.

NextDenovo contains two core modules: NextCorrect and NextGraph. NextCorrect can be used to correct TGS long reads with approximately 15% sequencing errors, and NextGraph can be used to construct a string graph with corrected reads. It also contains a modified version of minimap2 for adapting input and output and producing more sensitive and accurate dovetail overlaps, and some useful utilities (see here for more details).

Address of the bookmark: https://github.com/Nextomics/NextDenovo

Bienko and Crosetto Labs

Fri, 12 May 2017 07:42:15 -0500

We are two groups of scientists doing frontier research in quantitative biology and biomedicine. The Bienko group is interested in exploring the fundamental design principles controlling how DNA is packed in the eukaryotic nucleus and its relation to gene expression regulation. The Crosetto group engineers new molecular methods for single-cell and spatially resolved omic measurements of DNA, RNA, and proteins, with a strong focus on tumor heterogeneity. By sharing ideas and resources, we work synergistically towards a more quantitative understanding of life’s processes in healthy and diseased conditions.

https://bienkocrosettolabs.org/

MEC: Contig Misassembly Correction

BioStar — Tue, 04 Feb 2020 23:40:49 -0600

MEC, to identify and correct misassemblies in contigs. Firstly, MEC takes fragment coverage as the feature to detect the candidate misassemblies. Then, it can distinguish a large number of false positives from the candidate misassemblies based on the distribution of paired-end reads and the statistical analysis of GC-contents. We apply MEC to four real contig datasets, and carry out experiments to analyze the influence of MEC on scaffolding results, which shows that MEC can reduce misassemblies effectively and result in quantitative improvements in scaffolding quality. MEC is publicly available for download at https://github.com/bioinfomaticsCSU/MEC.

Address of the bookmark: https://github.com/bioinfomaticsCSU/MEC