BOL: Related items

The Institute for Molecular Bioscience (IMB), Bailey Lab

Sun, 14 Jul 2013 11:53:08 -0500

Pattern recognition and computational biology

MEME Suite software development; gene expression; mathematical modelling; gene regulation and transcription

Specialization:
Pattern recognition and modelling in computational biology

Link @ http://www.imb.uq.edu.au/tim-bailey

STUDENTSHIP and TRAINEESHIP @ University of Madras

Sat, 16 Nov 2013 19:27:40 -0600

Bioinformatics Infrastructure Facility
University of Madras
Chennai 600 025

Applications are invited for the STUDENTSHIP and TRAINEESHIP vacancies to carry out project/research work in the DBT - Bioinformatics Infrastructure Facility with consolidated stipend of Rs.5,000/- per month.

Essential Qualification

Student Trainee: Those who have completed M.Sc., Bioinformatics/Biophysics/Life sciences or Pursuing M.Tech., Bioinformatics/Biotechnology

Duration : 3-4 Months

Student Trainee: Those who are pursuing M.Sc Bioinformatics/Biophysics/ Life sciences/others

Duration : 2-3 Months

Mail your CV on or before 25th November 2013 to shirai2011@gmail.com and hard copy to "Dr. D. Velmurugan, Professor & Head, CAS in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai 600 025". Also, the applicants are requested to attend the interview on 29th November, 2013 at 11 A.M.

www.unom.ac.in/uploads/announcements/bifadvertisement_20131114080003_23240.pdf

Five points for bioinformatics software/tools

Jitendra Narayan — Mon, 05 Aug 2013 04:12:32 -0500

In the bioinformatics sector we mostly spend time on computational analysis of huge amounts of data and try to make sense of it, biologically. But, most of the newbie bioinformaticians are faced with dilemma when they receive biological sequence data for the first time. They mostly found confusing over open source, user friendly GUI, and commercial bioinformatics software. Don’t be surprise this is true and also not an easy task to decide, because analytical step is the most crucial part and believe to be the biggest bottleneck in publishing paper in high impact journals. Through this blog I would like to address the pros and cons of both kind of software/tools and try to assist (Hmmm not really, It looks convince) you to make decision on your software selections.

The most common newbie questions are:

Should I try to use these free open source programs? Why are we not trying GUI software for computational analysis? Should I use commercial bioinformatics programs/software?”

1. Let’s be open

We generally think free and cheap are useless. But this concept is not applicable when we discuss open source software. Mostly, the bioinformatics software is developed by highly competitive biological programmers who believe in open sharing of knowledge. They come under Open Bioinformatics Foundation or O|B|F which is a non-profit, volunteer run organization focused on supporting open source programming in bioinformatics. The best part about open source tools/software is that they’re free to download the source code and read exactly what the program does. If you are so inclined, you can view all of the parts of the program and see the logical flow of the pipeline. In addition, open source makes an excellent learning tool for any beginning bioinformatician. Moreover, you can modify existing open source programs to deal with cutting-edge problems or to customize your pipeline. Apart from your computational and analysis work, most of the reviewer also prefers the open source based results so that they can validate the results if validation required.

2. Code headache

As a bioinformatician you are supposed to know the basics of programming languages, and if you are not good at it, then please learn it as soon as possible because you are not a bio-analyst but biological programmers. The open source programs usually lack dedicated service and support teams (often because they were the product of an overworked doc/postdoc!) so you are responsible for troubleshooting your own errors most of the time. We commonly receive the HELP email to support and assist to setup the pipeline; you can also find this kind of request on any QA forum. I personally believe this coding horror brings the biggest downside of open-source programs; where you need some programming skills in order to implement the program in your pipeline. But, if you are not able to fix the pipeline and modify the open source code according to your requirements them you should re-think on your bioinformatician name tag!!!

3. Dive into the codes

Some of the biologist turn bioinformatician says “if you can do the same thing with commercial software then why to get migraine with weird codes”, well this statement looks to me that guys are keen to learn swimming but still don’t like to get wet. If you are still using paid software and doing your work by customer support and clicking some of the well-designed GUI button then perhaps you are not interested in learning and trying new and challenging bioinformatics works. You are missing the basic flavour of bioinformatics. Let’s dive into the coding world, I am sure your will enjoy it. I recommend your to swim freely in code’s sea, and enjoy the journey; do not merely watch it from the outside.

4. Paid does not mean better

The bioinformatics company which are specializes in bioinformatics solutions develop well designed/packed, user friendly software by using a large number of specialised scientist, programmers and support staff. They also provide good services to accomplice your biological analysis work. This means that if you hit a ‘snag’ with your data, help is likely only a phone call away! These companies price their products competitively against the cost of a dedicated bioinformatician. You may be able to afford the program, but not the additional staff! Additionally, most of the functionality that you need in your analysis is already coded into the program. Need to plot a graph? Just click this button right here. It is that easy. But, as a bioinformatician this is not generally well encouraged approach in biological analysis work, because the software is not available to everyone and your data can’t be validated. Moreover, there is very less chances that anyone will repeat your work or love to do similar kind of research (because not all the labs in the world are rich like yours).

5. Take a caution

In biological analysis work, in which you deal GB/TB of data are having maximum chances of getting errors, so please be careful and always cross check your data before coming to any conclusion. Even an error in two line code can alter your entire analysis and display weird results. Some of the scientist blindly believes on commercial software, which is entirely wrong. Using proprietary tools does not absolve you of the need to actually read and research the type of analysis that you are doing. This is particularly true in the case of genome assembly and annotation.

At the end, I would like to tell only one think that open source solutions allows you to do more cutting edge analysis than the commercial tools. So let’s go for it.

Disclaimer:

This is my personal view. I have nothing to do with any company or open source community. The views expressed on these pages are mine alone and not those of my current/past employers. I do reserve the right to remove comments left by spammers or off-topic comments.

Prime Minister’s 100k Genome Project

Jitendra Narayan — Thu, 08 Aug 2013 09:40:39 -0500

Genomics Ebgland is destined to sequence 100,000 patients over the next five year in England. A landmark project by british government.

Genomics England will play a key role in building on the UK’s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system – leading the global race for better tests, better drugs and above all better, more personalised care.

http://www.genomicsengland.co.uk/100k-genome-project/

What are the difference between BioRuby and BioGem?

Neel — Mon, 12 Aug 2013 09:27:57 -0500

I came across two diferent but matching term BioRuby and BioGem. What are the difference between these two term? If both are using same Ruby language for development then why did they develope two different biological packages.

Computational Biology in the 21st Century: Making Sense out of Massive Data

Thu, 29 Aug 2013 08:32:26 -0500

Computational Biology in the 21st Century: Making Sense out of Massive Data Air date: Wednesday, February 01, 2012, 3:00:00 PM Category: Wednesday Afternoon Lectures Description: The last two decades have seen an exponential increase in genomic and biomedical data, which will soon outstrip advances in computing power to perform current methods of analysis. Extracting new science from these massive datasets will require not only faster computers; it will require smarter algorithms. We show how ideas from cutting-edge algorithms, including spectral graph theory and modern data structures, can be used to attack challenges in sequencing, medical genomics and biological networks. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. Author: Dr. Bonnie Berger Runtime: 00:58:06 Permanent link: http://videocast.nih.gov/launch.asp?17563

BINC (BioInformatics National Certification) Website address

Kamalakshi Mukherjee — Wed, 14 Aug 2013 09:40:22 -0500

BINC (BioInformatics National Certification) is an initiative of Department of Biotechnology(DBT), Government Of India in coordination with Bioinformatics Center, University of Pune. The objective of the examination is to recognize trained manpower in the area of Bioinformatics. Currently, various Indian universities, Government and private institutions are involved in imparting courses in Bioinformatics in India.

Foreign nationals intending to have certification are eligible to appear for BINC examination.
Minimum qualification includes a degree from a recognized university/institute in the areas listed in FAQ.
Formal training in the area of Bioinformatics is not a prerequisite.
Note that the foreign students will only be certified by DBT and are not eligible for the cash award as well as junior research fellowship.

Address of the bookmark: http://binc.scisjnu.ernet.in/

Baumbach Lab

Wed, 21 Aug 2013 10:56:35 -0500

The Computational Biology research group was established in October 2012 at the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark (SDU). It emerged from the Computational Systems Biology group, founded in March 2010 at the Max Planck Institute for Informatics (MPII) and the Cluster of Excellence for Multimodel Computing and Interaction (MMCI) at Saarland University, Saarbrücken, Germany.

The group is headed by Prof. Dr. Jan Baumbach and currently hosts nine PhD students and one postdoctoral fellow at both, IMADA/SDU and MMCI/MPII.

More at >> http://www.baumbachlab.net/

Chang lab

Tue, 24 Sep 2013 17:25:49 -0500

The Chang lab is focused on how the activities of hundreds or even thousands of genes (gene parties) are coordinated to achieve biological meaning. We have pioneered methods to predict, dissect, and control large-scale gene regulatory programs; these methods have provided insights into human development, cancer, and aging. A particular interest is how cells know and remember their locations in the body, particularly with the help of long noncoding RNAs.

More at http://changlab.stanford.edu/index.html

PostDocs positions in computer science in HELSINKI, FINLAND

Fri, 06 Sep 2013 10:11:19 -0500

Several university departments in the Helsinki region, Finland, are looking for postdoctoral researchers in the field of computer science and information technology. Jobs are available at:
· Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki, http://www.hiit.fi
· Department of Computer Science, University of Helsinki, http://www.cs.helsinki.fi
· Department of Information and Computer Science, Aalto University, http://ics.aalto.fi
· Department of Computer Science and Engineering, Aalto University, http://cse.aalto.fi
· Department of Mathematics and Statistics, University of Helsinki, http://mathstat.helsinki.fi/english/

Why Helsinki?
The collaborating Aalto University and University of Helsinki form a leading hub of computer science and modelling, including Machine learning, Data mining, Algorithms, Computational Logic, Cloud computing, Distributed computing, Human-centric ubiquitous ICT, Bioinformatics, etc.
Helsinki region is a safe, pleasant and attractive place to live in, with well-functioning services such as public transport etc. Finland has a comprehensive social security and health care system, including exceptionally good parental leaves, and children's day care services.

Positions are offered in:
Algorithm engineering (String Algorithms group)
Algorithmic bioinformatics (Genome-Scale Algorithmics group)
Automated reasoning and search, especially propositional logic (Computational Logic group)
Computational astrophysics and/or data analysis (Computational Methods and Data Analysis for Astrophysics group)
Computational biology and statistical methods in bioinformatics (Computational Systems Biology group)
Computational creativity and data mining (Discovery group)
Dynamic and large-scale networked systems (Data Communications Software group)
Intelligent multimodal information access (Content-Based Image and Information Retrieval Group)
Machine learning and neuroscience (Statistical Machine Learning group)
Machine learning for structured data (Kernel Machines, Pattern Analysis and Computational Biology group)
Machine learning methods for infectious disease epidemiology (Bayesian Statistics Group)
Probabilistic modeling and machine learning (Complex Systems Computation group)
Statistical machine learning (Statistical Machine Learning group)
Analysing ubiquitous sensor data (HIIT-Wide Focus Area)
Interactive visualization (HIIT-Wide Focus Area)
Affective computing and BCI (HIIT-Wide Focus Area)
Intelligent user interfaces and/or recommender systems (HIIT-Wide Focus Area)
Information retrieval and HCI (HIIT-Wide Focus Area)
Machine learning and data analysis, especially information retrieval, HCI, text and context data (HIIT-Wide Focus Area)
Probabilistic modeling and data analysis for bioinformatics (HIIT-Wide Focus Area)

More at http://www.hiit.fi/postdoc-call-2013