The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.

Address of the bookmark: https://github.com/AusARG/pipesnake

Why Bioinformatics Matters More Than Ever

Every day, our world generates massive amounts of biological data—from genome sequences to microbiome profiles to real-time pathogen surveillance. Hidden within these datasets are the answers to some of the greatest challenges humanity faces: emerging diseases, antimicrobial resistance, environmental stress, genetic disorders, sustainable agriculture, and more.

Bioinformatics isn’t just a skill.
It’s the language of the future of biology.

By mastering it, you give yourself the power to:

Decode genomes and understand life at its most fundamental level

Identify patterns no microscope could ever reveal

Predict disease outbreaks before they occur

Accelerate drug discovery with computational precision

Contribute to open-source tools that empower scientists worldwide

You don’t just follow science—you drive it.

Every Expert Was Once a Beginner

Many newcomers feel intimidated. Command-line interfaces. R scripts. Python packages. Next-generation sequencing data. Complex machine learning models.

But here’s the truth: every bioinformatician started exactly where you are now—curious, unsure, but excited.

No one writes perfect code on day one.

No one understands genomics pipelines immediately.

What makes you a bioinformatician is not perfection, but perseverance.

When your script throws a cryptic error…
When your data refuses to format…
When your pipeline runs for 6 hours only to crash…

Remember: this is part of the journey.
Every error teaches you. Every retry strengthens you. Every breakthrough energizes you.

Bioinformatics Is Not Just a Career—It’s a Mindset

It’s the mindset of:

Problem-solving.

Continuous learning.

Turning chaos into clarity.

Seeing what others can’t.

Bioinformaticians are detectives of biological complexity. You sit at the intersection of innovation, using tools that can shape public health, medicine, agriculture, and ecology. Few fields give you such direct impact on the world.

Your Contribution Matters

As you work on your script, pipeline, genome, or model, remember:

Somewhere, your analysis might contribute to:

A new therapy

A faster diagnostic test

A better understanding of a pathogen

A more resilient crop

An open-source dataset that helps thousands

A discovery that rewrites textbooks

Your code may be small, but its ripple effect is powerful.

The Future Is Bioinformatics—And You Are Part of It

The world is shifting. Wet labs are integrating AI. Hospitals rely on genomic insights. Farmers use gene-level predictions. Governments monitor disease in real time. Students launch pipelines that become global tools.

This is a golden era—and you are not late.
You are exactly where you need to be.

Keep Pushing. Keep Learning. Keep Discovering.

Bioinformatics is a journey filled with challenges, but also with unmatched rewards.

So the next time you feel stuck, frustrated, or overwhelmed, remember:
You’re building the science of tomorrow.

Be proud. Stay curious. Keep going.
Your work matters more than you think.

Research Area:
pancreatic cancer; ovarian cancer; prostate cancer; bowel cancer; brain cancer; endometrial cancer; breast cancer; personalised medicine; high-throughput genomics

Link @ http://www.imb.uq.edu.au/sean-grimmond

Selected Topics:

Cluster Dynamics
Non-equilibrium Statistical Mechanics
Forced Systems
Hamiltonian Dynamics
Synchronization & Control
Genomics & Systems Biology
Computational Neuroscience
Econophysics

More @ http://www.jnu.ac.in/Conference/SCS2013/

Research Area

Developmental biology, Computational biology, Simulation modeling, Image data analysis

Link @ http://mysite.science.uottawa.ca/arolland/index.html

The main purpose of OSDDLinux is to provide an in silico platform for computer-aided drug design. This is a collection and compilation of large number of software and web services which will be directly or indirectly useful for researches working in the field of drug design/discovery. Overall objective of OSDDlinux is to promote open source in drug discovery, crowdsourcing and network based collobrations. Following are major features of OSDDlinux ... 

Find more @ http://osddlinux.osdd.net/index.php

unzip blatSrc35.zip

to unpack the archive. This gives a directory blatSrc now move into that directory.

#cd blatSrc

before you begin read the README file that comes with the source code.

One thing about building blat is that you need to set the MACHTYPE variable so that the BLAT sources know what type of machine you are compiling the software on.

on most *nix machines, typing

echo $MACHTYPE

will return the machine architecture type.

On my CentOS 6 based system this gave:

x86_64-redhat-linux-gnu

However, what BLAT requires is the 'short value' (ie the first part of the MACHTYPE). To correct this, in the bash shell type (change this to the correct MACHTYPE for your system)

MACHTYPE=x86_64
export MACHTYPE

now running the command:

echo $MACHTYPE

should give the correct short form of the MACHTYPE:

x86_64

now create the directory lib/$MACHTYPE in the source tree. ie:

mkdir lib/$MACHTYPE

For my machine, lib/x86_64 already existed, so I did not have to do this, but this is not the case for all architectures.

The BLAT code assumes that you are compiling BLAT as a non-privileged (ie non-root) user. As a result, you must create the directory for the executables to go into:

mkdir ~/bin/$MACHTYPE

If you are installing as a normal user, edit your .bashrc to add the following (change the x86_64 to be your MACHTYPE):

export PATH=~/bin/x86_64::$PATH

For me, though, this was not good enough. I wanted the executables in /usr/local/bin where all my other code goes. As a result I did some hackery...

There is a master make template in the inc directory called common.mk and I edited this file with the command:

vi inc/common.mk

I replaced the line

    BINDIR=${HOME}/bin/${MACHTYPE}

with

    BINDIR=/usr/local/bin

saved and quit (as this is in my path, I do not need to do anything else)

All the preparation is now done and you can create the blat executables by going into the toplevel of the blat source tree (for me it was /usr/local/src/blat/blatSrc, but change to wherever you unpacked blat into).

Now simply run the command:

make

to compile the code.

Blat installed cleanly and the executables were all neatly placed in /usr/local/bin/x86_64, just like I wanted.

now simply running the command:

blat

on the command line gives me information on blat and sample usage.

Blat is installed and it's installed properly in my system code tree!!!

In this tutorial, we will show you how to install and configure Elgg social networking platform on Ubuntu 20.04.

Prerequisites

• A fresh Ubuntu 20.04 VPS on the Atlantic.net Cloud Platform
• A valid domain name pointed to your server IP
• A root password configured on your server

Step 1 – Create Atlantic.Net Cloud Server

First, log in to your Atlantic.Net Cloud Server. Create a new server, choosing Ubuntu 20.04 as the operating system with at least 2GB RAM. Connect to your Cloud Server via SSH and log in using the credentials highlighted at the top of the page.

Once you are logged in to your Ubuntu 20.04 server, run the following command to update your base system with the latest available packages.

apt-get update -y

Step 2 – Install Apache, MariaDB and PHP

Elgg runs on Apache web server, is written in PHP, and uses MySQL/MariaDB as a database backend, so you will need to install the Apache, MariaDB, PHP and other required PHP extensions to your server. You can install all of them with the following command:

apt-get install apache2 mariadb-server php libapache2-mod-php php-common php-sqlite3 php-curl 
php-intl php-mbstring php-xmlrpc php-mysql php-gd php-xml php-cli php-zip unzip wget -y

After installing all the packages, edit the php.ini file and change some recommended settings.

nano /etc/php/7.4/apache2/php.ini

Change the following values:

max_execution_time = 300
memory_limit = 512M
upload_max_filesize = 100M
date.timezone = Asia/Kolkata

Save and close the file, then restart the Apache service to apply the configuration changes.

systemctl restart apache2

Step 3 – Create a Database for Elgg

Next, you will need to create a database and user for Elgg. First, log in to MySQL shell with the following command:

mysql

Once logged in, create a database and user with the following command:

CREATE DATABASE elgg;
CREATE USER 'elgg'@'localhost' IDENTIFIED BY 'secure-password';

Next, grant all the privileges to the elgg database with the following command:

GRANT ALL ON elgg.* TO 'elgg'@'localhost' IDENTIFIED BY 'secure-password' WITH GRANT 
OPTION;

Next, flush the privileges and exit from the MariaDB shell with the following command:

FLUSH PRIVILEGES;
EXIT;

At this point, the MariaDB database is created for Elgg.

Step 4 – Install Elgg

First, download the latest version of Elgg from its official website using the following command:

wget https://elgg.org/download/elgg-3.3.13.zip

Once the download is completed, unzip the downloaded file with the following command:

unzip elgg-3.3.13.zip

Next, move the extracted directory to the Apache root directory:

mv elgg-3.3.13 /var/www/html/elgg

Next, create a data directory and set proper ownership and permissions to the Elgg directory:

mkdir /var/www/html/data
chown -R www-data:www-data /var/www/html/elgg
chown -R www-data:www-data /var/www/html/data
chmod -R 755 /var/www/html/elgg

Once you are finished, you can proceed to the next step.

Step 5 – Configure Apache for Elgg

Next, you will need to configure Apache to serve Elgg. You can configure it by creating a new Apache virtual host configuration file:

nano /etc/apache2/sites-available/elgg.conf

Add the following lines:

<VirtualHost *:80>
ServerAdmin admin@example.com
DocumentRoot /var/www/html/elgg/
ServerName elgg.example.com
Options FollowSymLinks
AllowOverride All
ErrorLog /var/log/apache2/elgg-error_log
CustomLog /var/log/apache2/elgg-access_log common
</VirtualHost>

Save and close the file, then enable the virtual host and Apache rewrite module with the following command:

a2ensite elgg.conf
a2enmod rewrite

Finally, restart the Apache service to apply the changes:

systemctl restart apache2

Step 6 – Access Elgg Web Interface

Now, open your web browser and access the Elgg web interface using the URL http://elgg.example.com. You should see the Elgg welcome screen:

Address of the bookmark: http://christophergandrud.github.io/d3Network/

3D-Dock Suite

Global rigid search: FFTShape complementarity and electrostatics

Re-scoring and clustering. Refinement of interface side-chains

3D-Garden

Global rigid search in ensamble

Shape complementarity and Lennard–Jones potential

Side chain and backbone dihedral refinement

DOT

Global rigid search: FFTShape complementarity, electrostatics and VDWNone

Escher NG

Global rigid searchShape complementarity, hydrogen bonds and electrostatic

Integrated in VEGA

GRAMM 

Global rigid search: FFT. smooth protein surface representation for soft docking

Shape complementarity and Lennard-Jones potential

Clustering of conformations

GRAMM-X 

Global rigid search: FFT. smooth protein surface representation for soft docking

Shape complementarity and Lennard-Jones potentialminimization and re-scoring with multiple filters

HEX

Global rigid search: Fourier correlation of spherical harmonics

Shape complementarity

HADDOCK

Global rigid searchElectrostatic ,VDW and desolvation energy termsMD simulated annealing refinement . Filtering based on external data. 

ICM

Global rigid search: Monte CarloEmpirical scoring function

Clustering and selection of conformations. Refinement of interface side-chains and re-scoring

MolFit 

Global rigid search: FFTShape complementarity

Clustering of good solutions, filtering using a priori information and small, local rigid rotations around selected conformations

PatchDock

Global rigid searchShape complementarity and atomic desolvation energy

Clustering of conformations

PyDock

Global rigid search:FFTShape complementarity

rescoring by binding electrostatics and desolvation energy

RosettaDock

Local rigid search: Monte Carlo with low and high resolution structure representation levels

Different scoring parameters for the different resolutions 

ZDOCK

Global rigid search: FFTShape complementarity, desolvation energy, and electrostatics.

Energy minimization and re-scoringFree for academics

Point to note:

The proper treatment of flexibility in protein–protein docking is still an active field of research. You first should analyzed your proteins in order to define their conformational space and then choose the most suitable method for your docking problem.