BOL: Related items

Research Associate openings at IASRI, India

Fri, 10 Mar 2017 03:53:03 -0600

Research Associate (RA) Two (2)

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements.

Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics
Knowledge in computer programming, LINUX OS.
Expertise in use of R/other Bioinformatics software

More at http://iasri.res.in/employment/2017/cabin_advertisement_RA_SRF_YP_Mar2017.pdf

Phenomics of Moisture Deficit Stress Tolerance and Nitrogen Use December 31, 2019

Research Associate (RA) Two (2)

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or System Administrator/ Computer expert for database development, development of phenome data bank and virtual phenomics facility, data archiving and Efficiency in Rice and Wheat-Phase II (Funded by National Agricultural Science Fund, ICAR) Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements. maintenance; Development of image analysis algorithms, APIs and IAPs.

Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics
Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software & tools.
December 31, 2019

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science / Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements.

Knowledge of Statistical and Computational Genomics/ Bioinformatics.
Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software & tools.
March 31, 2020

Bioinformatics: Introduction to PERL

Archana Malhotra — Thu, 11 Jul 2013 09:49:37 -0500

This course is aimed at those new to programming and provides an introduction to programming using Perl. By the end of this course, attendees should be able to write simple Perl programs and to understand more complex Perl programs written by others. The course will be taught using the online Learning Perl materials created by Sofia Robb of the University of California Riverside. Further information is available.

NGS & Bioinformatics Summit Europe

Sat, 13 Jul 2013 17:02:34 -0500

NGS & Bioinformatics Summit Europe

Conference

7th to 8th October 2013
Berlin, Germany

Website: https://www.gtcbio.com/conference/ngseurope-overview
Contact person: Kristen Starkey

We welcome you to join us at GTC’s NGS & Bioinformatics Summit Europe on October 7-8, 2013 in Berlin, Germany.

Organized by: GTC
Deadline for abstracts/proposals: 7th September 2013

SNPGenie

Jit — Thu, 30 Mar 2017 17:38:02 -0500

SNPGenie is a Perl script for estimating evolutionary parameters, mainly from pooled next-generation sequencing (NGS) single-nucleotide polymorphism (SNP) variant data. SNP reports (acceptable in a variety of formats) much each correspond to a single population, with variants called relative to a single reference sequence (one sequence in one FASTA file). Just run the main script, snpgenie.pl, in a directory containing the necessary input files, and we take care of the rest! For the earlier version, see Hughes Lab Bioinformatics Resource.

Address of the bookmark: https://github.com/hugheslab/snpgenie

Boku Chair of Bioinformatics

Sun, 14 Jul 2013 12:37:23 -0500

The Bioinformatics group at Boku University has two main areas of interest, underpinning a common goal, the study of complex systems in living organisms. To overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes, novel views augmenting the classical gene by gene approaches are required. We combine
Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and
Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)

Link @ http://bioinf.boku.ac.at/

NGS teaching material

Jit — Wed, 05 Apr 2017 04:29:06 -0500

High throughput sequencing (HTS) technologies are being applied to a wide range of important topics in biology. However, the analyses of non-model organisms, for which little previous sequence information is available, pose specific problems. This course addresses the specific strengths and weaknesses of alternative HTS technologies, the computational resources needed for HTS, and how to analyze non-model species using HTS. The course consists of a practical training module, HTS bioinformatics training, and lecturing/seminars of HTS approaches specifically targeting non-model organisms.

Address of the bookmark: http://marinetics.org/teaching/hts/Assembly.html

6 PhD Students @ TU Dresden

Sun, 14 Jul 2013 13:42:06 -0500

At TU Dresden, Faculty of Computer Science, the DFG Research Training Group GRK 1907 “Role-based Software Infrastructures for continuous-context-sensitive Systems” offers the positions of 6 PhD Students (E 13 TV-L)

for applicants interested in performing high-quality research on the connection between software engineering, database systems, and theoretical computer science as well as their applications in bioinformatics and business informatics. The research programme will start on October 1, 2013 until 30.09.2016. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG).

This research programme is a joint activity of Professors Lehner, Assmann, Baader, Baier, Schill, Schlegel, Schroeder, and Strahringer at TU Dresden. Alongside their research, an individual mentoring and qualification approach are arranged with specialized courses that prepare them optimally for their research, a research seminar where they can meet internationally renowned researchers in the field, and soft skills and language courses.

Requirements: Applicants should have an excellent academic record, and hold a MSc (or an equivalent university degree) in computer science or related disciplines (such as mathematics, bioinformatics or business informatics). Fluency in spoken and written English is required. Applicants with a good knowledge of software engineering or one of the application areas mentioned above are preferred. TU Dresden is committed to increase the proportion of women in research.

Applications from women are particularly welcome. The same applies to disabled people.

Please send enquiries to: wolfgang.lehner@tu-dresden.de

Applications consist of a CV, the names of two referees, transcipts of documents summarizing their academic performance, and a statement of interest. Application by email in pdf format is preferred, and should be submitted to wolfgang.lehner@tu-dresden.de in an electronically signed and encrypted form by July 30, 2013 (stamped arrival date of the university central mail service applies). Alternatively, applications can be sent to: TU Dresden, Fakultät Informatik, Institut für Systemarchitektur, Prof. Dr.-Ing. Wolfgang Lehner, 01062 Dresden, Germany.

Shortlisted candidates will be invited to Dresden in the middle of August to give a presentation on their Master’s thesis and discuss their research interest with the participating professors. Candidates that have not yet finished their degree when they send in their application should send preliminary transcripts of their academic records as well as a letter by the thesis adviser that comments on their progress so far and on the expected date of completion of their MSc or equivalent degree.

UpSetR Shiny App!

Jit — Fri, 14 Apr 2017 06:19:54 -0500

UpSetR generates static UpSet plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.

To begin, input your data using one of the three input styles.

"File" takes a correctly formatted.csv file.
"List" takes up to 6 different lists that contain unique elements, similar to that used in the web applications BioVenn (Hulsen et al., 2008) and jvenn (Bardou et al., 2014)
"Expression" takes the input used by the venneuler R package (Wilkinson, 2015)

Address of the bookmark: https://gehlenborglab.shinyapps.io/upsetr/

The Laboratoire de genomique fonctionelle

Sun, 14 Jul 2013 13:03:18 -0500

One persistent challenge of post genome biology remains the determination of the functions of all potential genes. In mammals this task is formidable given that a single gene can produce numerous protein isoforms through alternative pre-mRNA splicing. Protein isoforms from a single gene can have diverse, and in some cases antagonistic, functions. AS plays a pivotal biological role in protein diversity and developmental regulation. It is now believed that AS occurs in up to 74% of human genes, making it more of a rule than an exception.

Link @ http://lgfus.ca/public/

DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies

Jit — Wed, 19 Apr 2017 10:09:51 -0500

DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies

Our work is published in Scientific Reports:

Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).

http://www.nature.com/articles/srep31900

The manual can be downloaded from:

https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx

To use precompiled versions,please go to:

https://github.com/yechengxi/DBG2OLC/tree/master/compiled

Address of the bookmark: https://github.com/yechengxi/DBG2OLC