Address of the bookmark: http://christophergandrud.github.io/d3Network/

Eligibility:
M.Sc. in any stream of Life Sciences with minimum 55% marks.

Desirable:
Candidates having experience in Molecular Spectroscopy, Protein Folding and Bioinformatics will be preferred.

Interested candidate may appear in the walk in Interview conducted on September 16, 2014 (Tuesday) 11:00 AM in the Director's Office, Centre for Interdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025.
Candidates are required to bring a set of Xerox copy of their recent CV and qualifying degree (certificate/mark sheet) along with original documents. NoTA/DA will be paid.

For any further information you may e-mail to: mihassan@jmLac.in

Read more at http://jmi.ac.in/upload/advertisement/jobs_cirbs_2014september8.pdf

What Is Julia Language?

Julia is a programming language that came into the limelight in 2012. It is a general-purpose programming language that was designed for solving scientific computations. Julia was meant to be an alternative to Python, R and other programming languages that were mainly used for manipulating data. This is because it has numerous features that can minimize the complexities of numerical computations. 

Julia optimizes on the best features of Python and R while at the same time overlooks their weaknesses. This explains why it is viewed as an alternative to these programming languages. For instance, it utilizes the readability and simplicity of Python then performs faster.

Julia is the most preferred programming language for data scientists and mathematicians. This is because its core features are similar to the ones that are used on most data software. Also, the language is ideal for these two subjects because its syntax is similar to the standard mathematical formulas.

Key Features Of Julia Language
Uses JIT Compilation
Parallelism
Dynamic Typing
Simple Syntax
Allows Metaprogramming
Accessible to Libraries
-1-Array Indexing

Julia Vs Python And R Programming Languages
1. Speed
Julia is faster than both Python and R. This is a very critical aspect that is given special attention in the big data programming. The high speed of Julia is because of JIT compilers. You will need to install external libraries on Python to achieve similar speed.

2. Syntax
Julia has a math-friendly syntax. The syntax of this programming language is similar to the mathematical formulas hence can be used to perform mathematical and scientific computations. This syntax makes it easier to learn than Python.

3. Parallelism
Although both Python and R use parallelism, Julia uses a top-level parallelism. Julia allows the processor to perform to the optimum level than what Python and R can achieve.

4. Versatility
Julia programming language is more versatile than Python and R. It allows a programmer to move from different codes and functions with ease.

The only area that Python and R are superior to Julia is in terms of community. Given that Julia is a new programming language, it has a small community as compared to others which have been around for years.

In overall Julia programming language is a better alternative that you can use to handle Big data projects. Despite having a small community, it is one of those programming languages that you can easily learn.

(Deemed University)

Hamdard Nagar, New Delhi – 110 062

R E C R U I T M E N T

(Advertisement No. 5/2014)

Applications on prescribed form are invited for filling up the following teaching positions in the Department of Biotechnology, Faculty of Science in the university. Eligible candidates may apply on or before 30.09.2014.

1. Professor/Associate Professor - One in Pay Band of Rs. 37400-67000+ AGP Rs.10000/9000

2. Assistant Professor - Two in Pay Band of Rs. 15600-39100+ AGP Rs. 6000/-

ASSISTANT PROFESSOR – 02 (including 01 SFS)

Specialization : Bioinformatics

Qualification and Experience :

Ph.D. in Biotechnology or an allied discipline with M.Sc. in Biotechnology/ Biochemistry in the First division or equivalent grade from a recognized University/ Institute.

NET in Life Science or allied discipline in addition to the above qualification.

Experience : At least two years of Post-doctoral teaching and/or research experience in Bioinformatics or relevant field in a UGC recognized Institution of repute or international research institute/ University. Proof of research to be evidenced by publications in SCI-indexed journals of high impact factor as the first or corresponding author.

Note : University may consider exempting candidates from NET, who has been awarded Ph.D. degree from ‘A’ Grade accredited University following the procedure as notified by the UGC in its Regulations of 2009 and adopted by Jamia Hamdard.

For more information: http://www.jamiahamdard.ac.in/PDF/Online%20application%20form%20_Teaching_1.pdf
http://www.jamiahamdard.ac.in/PDF/PBAS.pdf

Features

• Linear representation of several segments of DNA
• Comparisons represented by areas between the segments (like Artemis, for example)
• Reads from common formats: Genbank, EMBL, blast, Mauve, and from user-generated tab files
• Plot several subsegments of the same segment on the same line, separated by a //
• Automatic or manual placement of the segments on the plot
• Add annotations to all the lines
• Create smart, automatic annotations for genomes, based on gene names
• Add a user-generated tree
• Add a global scale or a scale to each line
• Use user-defined graphical functions to represent genes

Address of the bookmark: http://genoplotr.r-forge.r-project.org/

Functional and Comparative Genomics

http://jp.senescence.info/
http://www.senescence.info/
http://www.liv.ac.uk/integrative-biology/staff/joao-de-magalhaes/

Address of the bookmark: https://cran.r-project.org/web/packages/alluvial/vignettes/alluvial.html

Extent of employment: 30 Hours per Week
Duration of employment: 1st of October 2015 to 30th of September 2019
Gross monthly salary and pay grade in terms of collective agreement for university staff (payable 14 times per year): B1, € 1.997,20

Responsibilities
The successful candidate (f/m) will pursue a Ph.D. project related to the interpretation of plant genome and transcriptome sequencing data from next-generation sequencing (NGS) platforms. In particular, the candidate will characterize the unexplored genome of quinoa, a crop plant of long-standing tradition in Latin America. We collaborate with research partners in Austria and abroad, and the candidate’s project will be of central importance in the context of this research network.

Required skills and qualifications
We are looking for a graduate student (f/m) with a Master’s degree in bioinformatics or in a related field, solid programming skills (e.g. developing sequence analysis tools), experience with the analysis of NGS data sets, understanding of lab methods and knowledge of genomics/transcriptomics. The group has successfully performed several projects using NGS technology. We have recently published the reference genome sequence of sugar beet (Dohm et al., Nature, 2014), a crop plant closely related to quinoa (same family, but different genus). Not yet published is a quinoa genome assembly that we have generated, and which will serve as the starting point of the candidate’s project. We are a multidisciplinary team and offer work in a lively and friendly atmosphere, and state-of-the-art computing infrastructure. We are looking forward to expanding our team by a dedicated and strongly motivated person with a distinct interest in the challenges of plant genomics.

Applications can be submitted until: 16th of August 2015

University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.

Please send your job application (incl. letter of motivation, CV, summary of Master’s thesis and contact details for two referees) to Personnel department, University of Natural Resources and Life Sciences, 1190 Vienna, Peter-Jordan-Straße 70; E-Mail: kerstin.buchmueller@boku.ac.at. (Reference code: 59)

We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.

www.boku.ac.at

https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8

Address of the bookmark: http://efs.heiderlab.de/

• Updated human gene set (GENCODE 21)
• Updated rat gene set including manual annotation from HAVANA
• New species: Vervet-African green monkey
• Imported Transcript Support Levels (TSLs) from UCSC for human and mouse
• Imported APPRIS flag for human and mouse
• Updated Amazon molly gene set

Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/