1️⃣ Data Analysis for the Life Sciences
A fantastic starting point to learn statistics, R programming, and exploratory data analysis in the context of biology. The best part? It’s available free online from HarvardX.

2️⃣ Practical Computing for Biologists
The very first book I picked up when I started learning computational biology. It’s beginner-friendly and focuses on essential computing skills every biologist needs.

3️⃣ A Primer for Computational Biology
An open-access, hands-on introduction to computational biology concepts and coding techniques. Perfect if you want to learn through real examples.

4️⃣ Computational Genomics with R
For those who already know R and want to dive deeper into genome-scale data analysis, from sequence alignment to gene expression.

5️⃣ The Biologist’s Guide to Computing
Bridges the gap between biological problems and computational thinking, making it easier for life scientists to approach programming and data analysis.

6️⃣ Bioinformatics Data Skills
A must-read to sharpen your bioinformatics toolkit — from command-line skills to reproducible research workflows. Ideal once you’ve covered the basics.

7️⃣ Bioinformatics Workbook
A practical tutorial series to help scientists design bioinformatics projects, analyze data, and understand best practices.

8️⃣ Modern Statistics for Modern Biology
An essential guide to modern statistical methods applied to biology, blending theory with hands-on examples in R.

9️⃣ Algorithms on Strings, Trees, and Sequences by Dan Gusfield
A classic reference for anyone wanting to understand the algorithms behind sequence alignment, genome assembly, and biological data structures.

People using computers were often seen
as helpers, not leaders—
useful, but not essential.

Sometimes, the criticism was direct.
Sometimes subtle.
But the message was the same—
this work doesn’t really count.

Then biology changed.
The questions became bigger,
and experiments alone
were no longer enough.

Organizing knowledge by hand worked once.
Now it needs computers—
to handle scale, speed, and complexity.

Some patterns are simply invisible
if you look at one sample.
You need many—
and the right tools to understand them.

So we started building maps—
of genomes, cells, and systems.
Not perfect,
but extremely useful.

Ideas also had to become clearer.
It’s no longer enough to say something sounds right—
you have to measure it.

The divide between “types” of biologists
never really made sense.
We are solving the same problems—
just in different ways.

Progress didn’t wait for agreement.
It moved forward with data,
with code,
and with careful analysis.

What matters now is simple:
• Biology depends on computation
• Coding is an important skill
• Statistics helps us think clearly
• And the people building these tools
are shaping the future of science

Disclaimer: This cartoon is solely designed to create humour and fun, not to offend any computer experts.

More at https://sites.temple.edu/liberles/

Breitbart lab is located in the College of Marine Science at the University of South Florida. She is chosen as top "10 Brilliant" scientist by Popular Science magazine.
http://www.popsci.com/science/article/2013-09/mya-breitbart

Lab Link:
https://sites.google.com/site/breitbartgenomicslab/
http://www.marine.usf.edu/faculty/mya-breitbart.shtml

Name of the fellowship: Junior Research Fellow (JRF) / Project Fellow

Title of the project: Genome-wide Mapping of Murine Specific Dengue T-cell Epitopes: Computational Prediction, Identification and use as Candidate Vaccines

Duration: 3 years

Fellowship: Rs. 18,000 for first 2 years and Rs. 20,000 for 3rdyear (for M.Tech. candidates)

Rs. 16,000 for first 2 years and Rs. 18,000 for 3rdyear (for M.Sc. candidates with NET qualification)

Rs. 8,000 for first 2 years and Rs. 10,000 for 3rdyear (for M.Sc. candidates without NET qualification)

Qualifications: M.Tech. in Biotechnology / M.Sc. in any branch of Life Sciences

Desirable Experience: Minimum of two years research experience in any of the following areas: Immunology / Microbiology / Gene Manipulation / Bioinformatics

Interested and eligible candidates may apply with their resume along with relevant documents and a passport size photograph to the Principal Investigator by post (or e-mail) on or before December 31, 2013. Only short listed candidates will be called for written test and/or interview. Selected candidate may register for PhD in Kalasalingam University. No TA/DA will be paid for attending interview.

Dr. K. Sundar
Principal Investigator (SERB Project)
Department of Biotechnology
Kalasalingam University
Krishnankoil – 626126, Tamil Nadu
sundarkr@klu.ac.in

http://www.bccs.uni.no/units/cbu/research/rehmsmeier/

- Budapest Reference Connectome: View a parametrizable connectome (brain graph).
- AmphoraNet: The webserver implementation of the AMPHORA2 workflow for phylogenetic analysis of metagenomic shotgun sequencing data.
- AmphoraVizu: Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet.
- SCARF: Free online association rule mining tool.

More at: http://pitgroup.org

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Address of the bookmark: https://www.coursera.org/course/ads1