<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/938?offset=190 https://bioinformaticsonline.com/bookmarks/view/26453/stacks Wed, 24 Feb 2016 15:52:30 -0600 https://bioinformaticsonline.com/bookmarks/view/26453/stacks <![CDATA[Stacks]]> Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.

More at http://catchenlab.life.illinois.edu/stacks/

Address of the bookmark: http://catchenlab.life.illinois.edu/stacks/

]]> Jitendra Narayan https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn Mon, 29 Feb 2016 17:39:24 -0600 https://bioinformaticsonline.com/bookmarks/view/26539/scikit-learn <![CDATA[scikit-learn]]> Machine Learning in Python

Simple and efficient tools for data mining and data analysis
Accessible to everybody, and reusable in various contexts
Built on NumPy, SciPy, and matplotlib
Open source, commercially usable - BSD license

More at http://scikit-learn.org/stable/index.html

 

Address of the bookmark: http://scikit-learn.org/stable/auto_examples/index.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool Wed, 06 Apr 2016 19:06:48 -0500 https://bioinformaticsonline.com/bookmarks/view/26927/phylographer-graph-visualization-tool <![CDATA[PhyloGrapher - Graph Visualization Tool]]> PhyloGrapher is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).PhyloGrapher is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use PhyloGrapher to visualize any type of relations between elements. 

More at http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html

Address of the bookmark: http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/opportunity/view/29915/professor-all-levels-in-bioinformatics-and-computational-biology Tue, 22 Nov 2016 05:43:38 -0600 <![CDATA[Professor (all levels) in Bioinformatics and Computational Biology]]> King Abdullah University of Science and Technology (KAUST) (kaust.edu.sa) is seeking a highly motivated and skilled faculty member for the Bioinformatics track whose research focuses on development of methods and tools for Bioinformatics and Computational Biology.
KAUST is an international, graduate-level research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Located on the shores of the Red Sea in Saudi Arabia, KAUST offers superb research facilities, generous assured research funding, and internationally competitive salaries, attracting top international faculty, scientists, engineers, and students to conduct fundamental and goal-oriented research to address the world’s pressing scientific and technological challenges in the areas of food, water, energy, and the environment.
The successful applicant is expected to develop world-leading research in domain of bioinformatics/computational biology with focus on development of novel computational approaches for efficient and accurate methods of analyzing biological phenomena at molecular level. The faculty member will be part of the Computational Bioscience Research Center (CBRC) within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. The position will remain open until filled.

Requirements:

PhD or equivalent in a Computer Science, Mathematics or Engineering discipline. Candidates should be well-established within the research field relevant to the position grade. They should demonstrate original research and experience at the highest international level.

Responsibilities and tasks:

Research competence in the following areas is preferred:
Analysis of next generation sequencing (NGS) and other ‘omics’ data (e.g. CAGE, ChIP-Seq, DHS, RNA-Seq, Ribo-Seq, proteomic, metabolic and NMR spectra, etc.).
Signaling, regulatory and metabolic pathways analysis.
Development of tools (web-based and standalone) suited for efficient computational biology/bioinformatics.


Visit cemse.kaust.edu.sa to apply.

]]> https://bioinformaticsonline.com/blog/view/30874/important-journals-blogs-and-forums-for-bioinformaticians Wed, 08 Feb 2017 09:15:31 -0600 https://bioinformaticsonline.com/blog/view/30874/important-journals-blogs-and-forums-for-bioinformaticians <![CDATA[Important Journals, Blogs and Forums for Bioinformaticians]]> Journals. Most journals have RSS feeds for their current updates.

Blogs. Some of these blogs are very relevant to bioinfo jobs. Others are more personal interest.

  • Variance Explained: David Robinson’s blog (Data Scientist at Stack Overflow, works in R and Python).
  • Global Biodefense: News on pathogens, outbreaks, and preparedness, with periodic posts on genomics and bioinformatics-related developments and funding opportunities.
  • In between lines of code: Lex Nederbragt’s blog on biology, sequencing, bioinformatics, …
  • Simply Statistics: A statistics blog by Rafa Irizarry, Roger Peng, and Jeff Leek.
  • Bits of DNA: Reviews and commentary on computational biology by Lior Pachter (fair warning: dialogue here can get a bit heated!).
  • Blue Collar Bioinformatics: articles related tool validation and the open source bioinformatics community.
  • Microbiome Digest – Bik’s Picks: A daily digest of scientific microbiome papers, by Elisabeth Bik, Science Editor at uBiome.
  • Living in an Ivory Basement: Titus Brown’s blog on metagenomics, open science, testing, reproducibility, and programming.
  • Enseqlopedia: James Hadfield’s blog on all things NGS.
  • Epistasis Blog: Jason Moore’s computational biology blog.
  • RStudio Blog: announcements about new RStudio functionality, updates about the tidyverse, and more.
  • nextgenseek.com: Next-Gen Sequencing Blog covering new developments in NGS data & analysis.
  • RNA-Seq Blog: Transcriptome Research & Industry News.
  • The Allium: We all need a little humor in our lives. Like The Onion, but for science.

Forums.

]]> Jit https://bioinformaticsonline.com/blog/view/428/five-unique-traits-of-effective-computational-biologist Thu, 11 Jul 2013 13:12:51 -0500 https://bioinformaticsonline.com/blog/view/428/five-unique-traits-of-effective-computational-biologist <![CDATA[Five unique traits of effective computational biologist]]> Bioinformatics research is driven by large set of software, scripts, and tools to analyse gigantic biological data. Being a great biological programmer or bioinformatician involves more than writing code that works. The biological programmers who rise to the top ranks of their profession are not only good programmer but also expert in biological stuff. Moreover, In order to be a good and effective biological programmer, you need to possess a combination of traits that allow your computational as well as biological skill, experience, and knowledge to produce working code. There are some technically skilled biological programmers who will never be effective because they lack the other important traits needed. Here are top five traits that are necessary to become a great biological programmer.

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.

]]> Jitendra Narayan https://bioinformaticsonline.com/researchlabs/view/851/the-institute-for-molecular-bioscience-imb-bailey-lab Sun, 14 Jul 2013 11:53:08 -0500 <![CDATA[The Institute for Molecular Bioscience (IMB), Bailey Lab]]> 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

]]> https://bioinformaticsonline.com/opportunity/view/6420/studentship-and-traineeship-university-of-madras Sat, 16 Nov 2013 19:27:40 -0600 <![CDATA[STUDENTSHIP and TRAINEESHIP @ University of Madras]]> 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.

Advertisement:

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

]]> https://bioinformaticsonline.com/blog/view/1212/computational-proteomics-lets-remember-the-basics Thu, 01 Aug 2013 17:24:20 -0500 https://bioinformaticsonline.com/blog/view/1212/computational-proteomics-lets-remember-the-basics <![CDATA[Computational Proteomics : Lets remember the basics]]> I spend some of my valuable time in computational drug designing sector. I remember my initial proteomics days, playing with interactive protein visualization software and dreaming big. Fortunately or unfortunately, I switched to genomics and handling the genomic floods in Petabytes which is expected to be in Brontobytes in coming years. Did I mention Brontobytes ??? Let me call to my server personnel … it gonna tsunami !!!!!

Today, refreshing my old memories I decided to blog about the basic knowledge of biochemistry and computational proteomics skills, but after I found several article on internet saying exactly what I had wanted to say I thought I might as well just redirect BOL's blog readers there instead:

Here is the list of website and videos links which provide a good resource for you basic chemistry need:

http://tecreativ.blogspot.co.uk/2012/09/funny-shortcut-remember-periodic-table.html

This blog have some specific hindi word to remember entire periodic table. I really like

Group 14 (C Si Ge Sn Pb) -> Sentence “Chemistry Sir Gives Sanki Problems”

Sanki is a hindi word which mean crazy :P

I found this link useful as well http://www.wikihow.com/Memorise-the-Periodic-Table

The eagle genomics group provide an element of bioinformatics in periodic tables. Yes you got it, this is not periodic table rather bioinformatics tools with periodicals

http://elements.eaglegenomics.com/

You can also try this video links, which provide you an overview with tricks on periodic tables:

http://www.youtube.com/watch?v=fLSfgNxoVGk

http://www.youtube.com/user/periodicvideos

For drug design educational material, software, tools, databses, viewer, file format and many more stuff at one place http://www.allfordrugs.com/drug-design/ I highly recommend you all computational drug designer to bookmark this page for future studies as well.

I just remember one of my mini project in which I use my flash knowledge (flash .. oh ya flash) to explain amino acids in interactive and user friendly manner. I can’t provide It right now, but promise you to provide a link in near future. I hope that you will enjoy my flashy creative skills :).

Moreover, I found some of very interesting tricks to remember all amino acids chemical formulae on youtube at

http://www.youtube.com/watch?v=gqrWb0fmzQ&list=PL6132651E70BB5575

http://www.youtube.com/watch?v=C2GfoGXfySQ&list=PL6132651E70BB5575


Key points for computer added drug designers?
1. A shortage of biochemistry skills means that you absolutely nowhere in understanding the key concept and do research.
2. Keep handy with complex mathematical formula, before merely running tools or software.
3. Dig it better and deeper guys .. design it.

]]> Jitendra Narayan https://bioinformaticsonline.com/researchlabs/view/4552/imtech-lab Sun, 15 Sep 2013 09:41:04 -0500 <![CDATA[IMTECH Lab]]> Computer Aided Protein Structure Prediction; Identification of Vaccine
Candidates (T-Epitope prediction); Analysis of Nucleotide/Protein Sequences; Development of Web Server/

Software; Creation of Public Domain Resources in Biology
Present Status::

Developing prediction methods for gene, beta-turn, secondary structure and MHC-binding sites.
Area of Interest ::

Comparison of force field simulations. Analysis of DNA-protein interactions using molecular mechanics methods.Drug Target Identification using in silico biology.

More @ http://www.imtech.res.in/bic/index.php?option=com_content&view=article&id=65

PIs: http://www.imtech.res.in/bic/index.php?option=com_content&view=article&id=69

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