• hist: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.
• gcp: K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.
• comp: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.
• sect: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.
• blob: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.
• filter: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
  • kmer: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.
  • seq: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.
• plot: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
  • density: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.
  • profile: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool
  • spectra-cn: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.
  • spectra-hist: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.
  • spectra-mx: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".

In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.

This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit: https://kat.readthedocs.org/en/latest/

https://academic.oup.com/bioinformatics/article/33/4/574/2664339 

Address of the bookmark: https://github.com/TGAC/KAT

Each node will host student interns interested in pursuing a research career in mathematical or computational biology at institutions located in its region.

Eligibility: Bachelors (3rd or 4th year) and Masters students

Average duration: 3 months (could be more in certain cases). These internships can be availed at any time during 2014 subject to consent from the faculty mentor.

Fellowship amount: Rs. 10,000 per month. In addition, outstation interns can receive up to Rs. 5000 per month for accommodation and Rs. 3000 for travel from and to their home place.

Application procedure: Apply online at http://nnmcb.appzone.co.in/

Deadline: February 10, 2014

Contact Information:

National Network for Mathematical and Computational Biology

Department of Mathematics

Indian Institute of Science

Bangalore 560 012

Tel: 080-2293 2893

Email: nnmcb@math.iisc.ernet.in

Paper: http://science.sciencemag.org/content/early/2018/10/10/science.aau4832

More at https://www.wired.com/story/genome-hackers-show-no-ones-dna-is-anonymous-anymore/

Recruitment for Research Associate and Project Assistant positions

Regional Centre for Biotechnology (RCB) is an autonomous academic institution established by the Department of Biotechnology, Govt. of India with regional and global partnerships synergizing with the programmes of UNESCO as a Category II Centre. The primary focus of RCB is to provide world class education, training and conduct innovative research at the interface of multiple disciplines to create high quality human resource in disciplinary and interdisciplinary areas of biotechnology in a globally competitive research milieu.

Research Associate (02 Position)

Consolidated emoluments Rs.22000/- + 30% H.R.A. p.m.

Essential: Ph.D. in Natural Sciences, minimum 60% marks in all qualifying exams and below 35 years of age.

Desirable: Prior experience at the PhD level in Biochemistry, Bioinformatics and Proteomics with a strong motivation for a career in research is highly desirable.

Strong PhD level training with proteins chemistry, protein purification and statistical analysis of proteomics or genomics dataset will be preferred. Either/ both qualifications should be substantiated by published papers.

Inter-Institutional Program for Maternal, Neonatal and Infant Sciences: A translational approach to studying preterm birth.

Principal Investigator: Dr. Dinakar M. Salunke

Applicants may apply along with the requisite documents (attested copies) pertaining to proof of date of birth, academic/professional qualifications, experience (if any), in the prescribed format available on our websites: www.rcb.res.in and www.rcb.ac.in. Applications should be sent to the Registrar, Regional Centre for Biotechnology, 180 Udyog Vihar Phase 1, Gurgaon-122016, Haryana, India, through Registered Post on or before Feb 28, 2014. A soft copy of the application should be sent by email to registrar@rcb.res.in. Incomplete applications or applications received after Feb 28, 2014 will not be entertained.

More at https://www.rcb.res.in/Advt-1._for_websites_PTB-revised.pdf

1. MSc. or B. Tech. or equivalent degree in Biotechnology or related life sciences discipline.
2. Strong aptitude for laboratory work and should be detail-oriented person.
3. Hands-on experience in basic molecular biology techniques.
4. Prior experience in working in a research laboratory or industry.
5. Basic IT skills that include familiarity with Microsoft Office packages.
6. Ability to carry out basic maintenance of general lab equipments and laboratory resources.
7. Ability to maintain accurate records of laboratory work.
8. Willingness to learn, and should be a team player.
Desirable Experience and Skills:
1. Familiarity with NGS technology.
2. Experience in preparation of NGS libraries.
3. Familiarity with Sanger sequencing technology (capillary electrophoresis based)

Remuneration: Remuneration will commensurate with expertise and experience.

How to Apply: Interested applicants fulfilling the criteria may send their detailed CV and a cover letter that explains their suitability for this position, in a single PDF, to Dr. Sreekanth Reddy at careers_bioit@ibab.ac.in. Last date for submission of application is 23rd February 2019. Please mention the position applying for in the subject line of the email.

About IBAB: The Bio-IT Centre at IBAB has state-of-art sequencing facility with the HiSeq 2500 and accessories such as Qubit, Covaris, Agilent 2200 TapeStation, Stratagene Mx 3000 for next generation sequencing, 3500 Dx Genetic Analyzer for capillary electrophoresis based sequencing, and HiScan for microarray imaging. The facility is fully operational and providing services to the scientific community. The Institute of Bioinformatics and Applied Biotechnology (IBAB) is a unique institute engaged in education, research and entrepreneur support programs and is based at Electronic City, Bangalore. IBAB’s mission is to catalyze the growth of the biotechnology and bioinformatics industries in India. To know more please visit: http://www.ibab.ac.in/index.php/bioit/

Genome Workbench can display sequence data in many ways, including graphical sequence views, various alignment views, phylogenetic tree views, and tabular views of data. It can also align your private data to data in public databases, display your data in the context of public data, and retrieve BLAST results.

Genome Workbench is built on the NCBI C++ ToolKit and uses cross-platform APIs for graphics. It runs on your local machine, and is available for Windows 2000/XP, Linux, MacOS X, and various flavors of Unix.

NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. Genome Workbench was developed entirely in-house at NCBI and makes use of the NCBI C++ ToolKit. The C++ ToolKit provides a convenient and flexible cross-platform API for managing system internals, database connections, network sockets, and the NCBI data model. In addition, the C++ ToolKit provides the Object Manager, which abstracts handling of sequences and sequence-related objects.

 New Features in Genome Workbench 2.7.15

• Multiple Alignment View: implemented adaptive feature display when zooming in
• Active Objects Inspector replaces Selection Inspector. New View should offer an improved selection context examination. See Using Active Objects Inspector tutorial for more details.
• Binary packages for Linux OpenSUSE 13.1 are now available

Bug Fixes and Improvements in Genome Workbench 2.7.15

• Fixed major issue with OpenGL overlay/scrolling. Could cause crashes or view scrolling irregularities
• Multiple Pane View: fixed crash on loading BLAST results
• Graphical Sequence View: fixed crash on zooming in and out, related to SNP track
• Graphical Sequence View: fixed Go To Position dialog to give better diagnostics in case of a user error
• Graphical Sequence View: PDF export fixed rendering of Markers with commas in the name
• Text View / Flat File: fixed Mac OS rendering issues
• Text View / Flat File: performance optimization, extended capabilities of real-time rendering of molecules to tens of thousands
• File Import: optimization improvement to speed up load of files containing multiple project items
• File Import: remapping stage now shows accession.version and description of molecules, instead of plain GI numbers
• Mac OS: improved tooltips for toolbar buttons
• Phylogenetic Tree Builder Tool: improved diagnostics of errors
• Multiple Alignment View: optimizations to avoid main GUI freezes
• Open Dialog: removed duplicate elements in table of genomes (load Genome)
• PDF export: fixed issue with XREF table errors
• Tree View: fixed issues with showing Force Layout progress on Mac OS
• Tree View: PDF export fixed issues for showing labels of collapsed nodes
• Tree View: added an option to stop layout
• Tree View: broadcasting mechanism fixed not to accumulate selected nodes

Reference:

NCBI news

http://www.ncbi.nlm.nih.gov/tools/gbench/

Age Limit: 35

How to Apply for the AIIMS Life Science Job:

Interested applicants are asked to send out a detailed CV to Dr Ashok Sharma (aioncoaiims@gmail.com). Laboratory of Chromatin and also Cancer Epigenetics, Department of Biochemistry with the subject line “Application for Scientist-B position for MeitY project” latest by January 01st, 2021.
Complete Information of the year of passing, experience, marks, etc. ought to be mentioned in the CV Incomplete. applications will certainly be rejected Just shortlisted applicants will be called for interview. Chosen candidates will certainly be intimated by email/phone.
No TA/DA will certainly be paid for appearing in the interview.
Note, The institute reserved the right to fill up or not to fill up the post advertised.

Emoluments: Rs. 56,000/- plus 24 percent HRA

Eligibility:
2nd class Master’s Degree with a PhD in a pertinent subject (Bioinformatics) from.a recognized University
1st class Master’s degree in Life Sciences (Bioinformatics) from a recognized university OR.
Bachelor’s Degree in Engineering or-Technology with minimal 60% marks from a recognized University or equivalent.

Desirable Qualifications:
Experience in Bioinformatics/NGS data. Analysis/System Biology/Computer Science/ statistics with experience in Machine learning/Al project.
Experience of Deep learning applications in biological data ( image/text).
Proficient in Rf Python machine learning libraries.
Prior experience in the cancer-related project (ML-based) will be advantageous.
Experience with PyTorch/TensorFlow will certainly be very desirable.
Applicant should have strong scientific writing as well as. verbal abilities.
Papers in sci-indexed journals demonstrating ML skill sets.
Database handling will certainly be plus yet not required.

More detail at https://www.aiims.edu/images/pdf/recruitment/advertisement/biochem-16-12-20.pdf

Applications are invited for the posts of one Junior Research Fellow in the DBT funded project entitled “Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.

Essential qualifications for JRF: First class M. Sc. / M. Tech in Bioinformatics. Knowledge of programming language, pearl, Statistics and database – HTML, CSS, Java script.

Desirable qualifications: Experience in handling next generation sequencing data

Age limit: 35 years maximum (5 year relaxation for SC/ST and women candidates) Emoluments: 16,000 + 30% HRA.

The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.

Those who are interested in pursuing Ph.D with strong research aptitude are preferred.

Interested candidates may attend the Walk in interview on 25th March 2014 along with the duly filled application forms (format in the following page) with all the relevant documents.

Venue: Division of Nematology, Indian Agricultural Research Institute, New Delhi 110012 (Room No. 306, 3rd floor, LBS building)

Reporting Time: Interested candidates should report strictly between 10.00 to 10.30 AM.

Interview time: 10.30 AM

Short-listed candidates will be called for interview at New Delhi. However, no TA and DA will be paid for attending the interview.

Advertisement:

https://www.iari.res.in/files/JRF_Nema-07032014-20140307-170017.pdf

Additional Information:

If you have any questions about scientific aspects of this position, please contact Prof. Lars Bertram, head of LIGA (lars.bertram@uni-luebeck.de).

Please contact Ms. Anna Wolbert for further questions about administrative details (recruiting@uksh.de).

Weitere Informationen erhalten Sie auch unter www.uksh.de/karriere.

Wir freuen uns auf Ihre Bewerbung bis zum 15.03.2020 unter Angabe unserer Ausschreibungsnummer 20190570.119.CL.

is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.
Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.

Required Qualifications:
• Ph.D. in plant computational biology or bioinformatics.
• Experience in a high performance computing environment.
• Perl, Python and Java programming experience
• Data management and database development experience

Desired Qualifications:
• Parallel computing experience
• Experience working in a multidisciplinary environment

Contact Information
South Dakota State University
Plant Science
Anne Fennell
anne.fennell@sdstate.edu
Tel. Number: 605-688-6373
http://www.biosntr.org