BOL: Related items

Bioinformatics 101 - Running BLAST

Tue, 03 Sep 2013 14:59:50 -0500

How to format the database for BLAST, run the command, view the output file, and use BioPerl and Perl to parse the output. By David Francis, Ohio State University. Delivered live at the Tomato Disease Workshop 2010. For more information, please visit http://www.extension.org/pages/32521/bioinformatics-101-video.

Courses to Get You Started with Bioinformatics

LEGE — Tue, 30 Sep 2025 13:07:19 -0500

Bioinformatics is now at the heart of modern biology and medicine. From decoding genomes and predicting antimicrobial resistance, to developing personalized medicine and advancing evolutionary research, computational skills are no longer optional — they are essential.

Yet, for many students, biologists, and even computer scientists, the question is: “Where do I begin?” With so many platforms, books, and tutorials available, it’s easy to feel overwhelmed.

To make it easier, I’ve compiled 10 excellent resources — ranging from beginner-friendly introductions to advanced computational genomics courses. Many of these are freely available, created by pioneers in the field, and widely used in classrooms and research labs worldwide.

Whether you are a complete beginner or looking to strengthen your foundations, these courses will help you build the skills needed to analyze biological data, design workflows, and think computationally about complex biological systems.

1. HarvardX Data Analysis for Genomics by Rafael Irizarry

From the almighty Rafa, this set of online courses (via edX/HarvardX) is a classic starting point for genomic data science and bioinformatics.

2. Applied Computational Genomics – Aaron Quinlan

Aaron Quinlan (creator of bedtools and many other tools) has made his course materials open. A practical, tool-driven genomics introduction.

3. Bioinformatics Algorithms (Coursera + Companion Book)

Find the highly visual video classes on Coursera, backed by the popular Bioinformatics Algorithms book.

4. The Biostar Handbook

Not a course per se, but a hands-on manual by Istvan (founder of Biostars.org) that’s even used in classes at Penn State.

5. Introduction to Bioinformatics and Computational Biology (by Shirley Liu)

A comprehensive introduction from Shirley Liu’s lab (Harvard DFCI). Covers both theory and computational practice.

6. Data Carpentry: Genomics Workshops

Community-driven training workshops that focus on practical, reproducible research. I was honored to serve as curriculum committee chair here.

7. Computational Genomics: Applied Comparative Genomics

From the Schatz Lab — applied comparative genomics with real-world data.

8. Introduction to Computational Biology (Mike Love, creator of DESeq2)

This course bridges statistics, biology, and computation — a solid primer for anyone entering computational biology.

9. MIT Computational Biology (6.047 / 6.878 / HST.507) by Manolis Kellis

Covers genomes, networks, evolution, and health. A deep-dive from MIT’s OpenCourseWare archive.

10. An Introduction to Applied Bioinformatics

An interactive textbook with Python code, designed for practical applied bioinformatics learning.

Python and BioPython Tutorial

Manshi Raghubanshi — Fri, 23 Aug 2013 06:47:40 -0500

A quickstart tutorial that allows to become familiar with the Python language. The exercises expect knowledge of basic concepts of programming. A group of 2nd year computer science students with no previous Python knowledge required 60'-90' to complete the exercises. With about 3 hours time, the exercise is suitable for non-programmers as well.

Address of the bookmark: http://www.biotnet.org/training-materials/python-programmers

Comparative genomics of gene expression lab

Wed, 09 Sep 2026 03:35:46 -0500

The core expertise of the lab is comparative genomics. We combine evolutionary bioinformatics and molecular biology to understand the mechanism, function and evolution of genes.
We study the processes of gene expression and protein synthesis, and we are particularly interested in the phenomenon of translational recoding (programmed exceptions to the genetic code). For more information, see Research.

More at https://www.mariottigenomicslab.com/

Research Project Posts for CSIR Project, Delhi

Tue, 27 Aug 2013 04:31:41 -0500

Positions Open For Temporary Research Project Posts for CSIR Project, Delhi
CSIR is looking for bright young candidates to get involved in building algorithms and platforms for large biological data analyses in the areas of comparative genomics, computational workflows, disease association studies, simulating virtual organelles, etc. Anyone who fulfills the eligibility criteria mentioned below may appear for a walk-in interview on 3rd September 2013 at CSIR Headquarters, Anusandhan Bhawan, 2 Rafi Marg, Delhi – 110001.
you can go to link for details or download PDF

http://www.csir.res.in/External/Heads/aboutcsir/announcements/ProjectPost_130813.pdf

What Junk DNA? It’s an Operating System

Rahul Agarwal — Mon, 19 Aug 2013 15:24:26 -0500

The report adds to growing experimental support for the idea that all that extra stuff in the human genes, once referred to as “junk DNA,” is more than functionless, space-filling material that happens to make up nearly 98% of the genome. The paper adds to a growing body of knowledge establishing a considerable role for this material in the regulation of gene expression and its potential role in human disease.

Address of the bookmark: http://www.genengnews.com/keywordsandtools/print/3/32115/

Bioinformatics Algorithm Demonstrations and Tutorials

Jitendra Narayan — Thu, 29 Aug 2013 09:23:51 -0500

Abstract

This project presents demonstrations of selected computer science algorithms important in bioinformatics, implemented in the spreadsheet program Microsoft Excel. Spreadsheets provide an interesting platform for demonstration of algorithms, since various steps of the calculations can be exposed in a manner that is easily comprehensible to users with little programming experience. The algorithms demonstrated include two approaches to approximate string matching (dynamic programming and Shift-AND numeric approximate matching), Hierarchical Clustering (used in phylogenetic studies and microarray analysis of gene expression), a Naive Bayes Classifier for simulated microarray gene expression data, and a simple Neural Network. These demonstrations are designed to serve as instructional aids in bioinformatics courses.

Tutorial @ http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsInExcel.zip

One of the best resource for online bioinformatics learning is https://stepic.org/Bioinformatics-Algorithms-2 Enjoy the online learning.

Reference : cybertory

" Please add your favourite bioinformatics algorithms and tutorial links below in the comment section, for the benefit of bioinformatics and computational biology community ".

Address of the bookmark: http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsExcelDoc.pdf

4273π: Bioinformatics education on low cost ARM hardware

Jitendra Narayan — Mon, 02 Sep 2013 07:02:43 -0500

Are you teaching bioinformatics at universities and found it complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. Hmm don't worry there is one new OS for the rescue. 4273π, an operating system image for Raspberry Pi based on Raspbian Linux. It provides an attractive, general-purpose computing environment, within which the course 4273π Bioinformatics for Biologists is embedded.

Though far slower than current desktop and laptop computers, the Raspberry Pi is notably faster than the Cray 1 supercomputer, a marvel of computer speed in its day. The Raspberry Pi approach includes all the benefits of the laptop approach, above, but at lower cost. In addition, the Raspberry Pi is a new and exciting computer system, which in itself can add interest to the course.

As the Raspbian operating system, Raspberry Pi firmware and hardware and 4273π Bioinformatics for Biologists teaching material develop, further releases of 4273π will be made available. It is anticipated that there will be a minimum of two releases per year during the next four years.

4273π is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost.

Descriptive paper @ http://www.biomedcentral.com/1471-2105/14/243

Image source: BMC Bioinformatics

RNA Bioinformatics and High Throughput Analysis Jena

Sat, 09 Nov 2013 20:03:56 -0600

Research Topics:

High Throughput Sequencing Analysis
Comparative Genomics
Identification and Annotation of Non-coding RNAs
Bioinformatic Analysis and System Biology of Viruses
Coevolution of Proteins and RNAs
Algorithmic Bioinformatics
Phylogenetic Analysis

http://www.rna.uni-jena.de/index.php