Address of the bookmark: https://arvados.org/

1. Learn and get updated

Some of the bad biological programmers only learn new technical or non-technical things when it’s absolutely necessary. The good biological programmers learn new technical skills proactively. But great biological programmers not only learn new technical skills on their own but also learn non-technical skills, and have an open mind to sources of knowledge that others may shut out.

In other concrete term, the bad biological programmer learn Perl's regular expression when they started a project on comparative genomics; the good biological programmer learned it a year before because it looked interesting; and the great biological programmer also read about the BioPerl packages, genomics, DNA string, genomic theories, or some similar course of study so that they could understand the results and explain it biologically.

2. Not a merely coder!!!

I often encountered with biological programmer who call themself a hard-core computer programmer and avoid biology. I can almost guarantee that if you are one of them then you are not doing research but merely writing "dry" codes.

According to my supervisor most of the computational biologist, don't know what they are doing biologically. Even they struggle to explain their own programs output and results. Therefore, It is highly advisable to learn basic of biology which can assist you to explain the result and understand your discovery. Always remember you are a researcher not a coder.

3. Be Social with biologist

The computational biologist spends most of the time in from of computers, writing codes. They always think their job is to produce working codes, not technical research perfections. But, they are completely wrong. You should not forget that apart from your computational skills you also need some biologist, other than your supervisor, to explain and make you understand the complex biological mechanism.

I highly recommend your to interact with biotech researchers and learn how do they explain their one graph (which they generally produce after one year of work) biologically. Remember, the origin of your research project is complex biological phenomenon, which is more complex than that of your limited programming rules.

4. Do not search, research for answers

Researching for answers means more than typing several keywords into a search engine or posting a question at Stack Overflow or the BioStars forums. I have entered problems into search engines that generate no results, and every question I posted on Stack Overflow or the BioStars forums never got anything resembling an answer, yet I solved the issues and moved on. I’m not a magician — I just know how to find answers or discover root causes.

Many problems are situational, and if you depend on search engines and forums, you can waste a lot of time going down a rabbit hole and possibly never getting a solution. Learn to perform root cause analysis, learn enough about the underlying system to look for other clues and solutions, and learn to take a long distance view of an issue before deep diving into it.

5. Love and defend your research

You cannot rise to the top in this research profession without loving your work. There are some very good “it’s just a job” biological programmers (I’ve been one at times), but if that is your outlook, you won’t be willing to do whatever it takes to succeed. This idea gets a lot of folks in a huff, because they feel it is a personal insult. “I’m a good programmer, but I have other priorities and can’t make work my life.” I understand completely; I have other priorities too. As much as I hate to say it, when I am passionate about my work, I am willing (though not eager) to abandon my other priorities to finish the job. It is not an insult to say that if you aren’t willing to pull out all the stops you can’t be the best, it is a fact.

You must be passionate about more than programming — you must also be excited about your research, the tools and technology you are using, and so on. I have seen very good and even great biological programmers operating at mediocre levels because something was not a good fit, such as they hated the project or were using a technology they disliked. Therefore, like your research project and get excited about your discoveries. You have not only to discover but also defend your finding with scientific words.

Thanks to all of you for reading.

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

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.

Advertisement:

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

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.

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/

The Taverna suite is written in Java and includes the Taverna Engine(used for enacting workflows) that powers both the Taverna Workbench(the desktop client application) and the Taverna Server (which allows remote execution of workflows). Taverna is also available as a Command Line Tool for a quick execution of workflows from a terminal.

Address of the bookmark: http://www.taverna.org.uk/

Gargi believes in its mission statement that every student who passes through the portals of the college emerges as a wholly developed individual symbolizing the spirit of enterprise and inquiry that characterizes Gargi.

Bioinformatics Infrastructure Facility (BIF), Gargi College, University of Delhi invites candidates for filling up the following purely temporary positions sponsored by DBT, New Delhi.

1. Name of the post: Traineeship
Essential Qualification: Post Graduate degree in Bioinformatics or any other branch of Life Sciences preferably with dissertation in Bioinformatics.
Desirable Qualification: Prior knowledge of programming languages such as C, VB, SQL etc. and software/database development.

2. Name of the post: Research Associate
Essential Qualification: PhD in Bioinformatics/Biological Sciences/Computer Science or allied sciences with proven experience in bioinformatics.

3. Name of the post: Studentship
Essential Qualifications: Final year Post Graduate students pursuing a degree in Bioinformatics or any branch of Life Science with knowledge of bioinformatics.

How to apply:
Interested candidates are required to appear for the walk in interview on 29th Aug, 2013 at 10.00 AM in Principal’s Office, Gargi College, Sirifort Road, N. Delhi-110049, with their CVs, original documents and a set of Photostat copies of all original documents.

http://www.du.ac.in/fileadmin/DU/students/Pdf/du/advt/2013/16082013_Gargi_RAplus2_Advt.pdf

POSITIONS OPEN FOR TEMPORARY RESEARCH PROJECT POSTS

(Date of interview 23rd September 2013 at 10:30 AM)

CSIR-Institute of Genomics & Integrative Biology (IGIB), desires to engage qualified incumbents on purely temporary basis as detailed below:

Project Code/Title (Project Code BSC0123)

Genome dynamics in Cellular Organization, Differentiation and Enantiostasis (GENCODE)

Project Fellow

First Class M.Sc./M.Tech in bioinformatics/Human Genetics/Genomics

Rs. 16,000/- + 30 % HRA per month

Sr. Project Fellow

First Class M.Sc./M.Tech in bioinformatics/Human Genetics/Genomics

With two years of experience in NGS data analysis.

Rs. 18,000/- + 30 % HRA per month

Age relaxation as per Govt. of India instructions.

Engagement is for the project and on behalf of the funding agency and the tenure shall be as mentioned above. The duration of the post is initially for One year or till the closing date of the project, whichever is earlier. Tenure may be extendable up to project duration. Contract may be terminated at any time by giving one-month notice by either side. The applicants will have no claim implicit or explicit for consideration against any CSIR/IGIB post.

How to Apply:

It is mandatory for eligible applicants to apply by both the processes as given below:

1. Sending the resume in MS Word format directly to hrd@igib.res.in (Mentioning the Project Code-Post Code in the Subject Line of the email example:GAP0059-1)

2. They also need to fill up proforma by clicking on the following link HR Online Form.

3. Candidate cannot apply for more than two posts.

Last date of receiving application is 02-09-2013.

No application would be entertained with result awaited status or after due date.

The email will be sent to the short listed candidates.

No TA/DA will be paid to the candidates to attend the interview. The engagement shall be as per guidelines of CSIR/Funding agency. Candidates will have an option to give reply in Hindi.

Note: The shortlisted candidates, who will receive the email for interview, have to report at 09:00 AM on the day of interview along with any Photo ID card and original certificates for entry purpose. Entry will be closed by 10:00 AM.

More @ http://www.igib.res.in/sites/default/files/23092013.htm