BOL: Related items

Gupta Lab

Sat, 29 Dec 2018 13:18:31 -0600

Work include (i) understanding the evolutionary relationships among different prokaryotic and eukaryotic organisms; (ii) Understanding the cellular functions of these lineage-specific signature proteins as well as lineage-specific conserved inserts and deletions in important housekeeping proteins by genetic and biochemical studies; (iii) Development of novel diagnostic methods (PCR based and immunological) for identification of different groups of organisms based upon these signature proteins and conserved indels; (iv) The use of these lineage-specific probes with predicitive ability to identify/explore the presence of different groups of organisms in metagenomic sequences from various environments.

https://fhs.mcmaster.ca/gupta-lab/index.html

Pimp your brain: Bioinformatics

Wed, 20 Aug 2014 22:09:21 -0500

Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research. In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO More videos are available on www.mpimp-golm.mpg.de

TMRCA Calculator

BioStar — Wed, 03 Feb 2021 05:07:30 -0600

This program calculates the probability that two people have a certain number of generations between them, based on the standard infinite alleles formula of Walsh. It calculates both the probability of being at an exact number of generations back to the Most Recent Common Ancestor (MRCA) of a certain pair of people and the cumulative probability that the actual number of generations is less than a certain value. Note that the convention using generations is changed from an earlier version of this calculator which used "transmission events". It can list both result types in a table or graph. In either case the horizontal axis stops at the point where the cumulative probability reaches 95% or 10 generations, whichever is longer, or an absolute max of 50,000. Beyond 90% the calculation becomes inaccurate.

https://clandonaldusa.org/index.php/tmrca-calculator

Address of the bookmark: https://clandonaldusa.org/index.php/tmrca-calculator

Useful link to teach evolution !

Abhi — Wed, 05 Oct 2022 18:29:30 -0500

Mimicry and other resources
Mimicry games:
Great Heliconius game:
http://heliconius.org/evolving_butterflies/
(See also 
https://royalsocietypublishing.org/doi/10.1098/rspb.2020.0014)
Other one, a bit less friendly:
https://ccl.northwestern.edu/netlogo/models/Mimicry
Camouflage practical
https://alexis-catherine.github.io/publication/natural-selection-and-camouflage/
(NetLogo also has one: 
https://ccl.northwestern.edu/netlogo/models/BugHuntCamouflage)
Peppered moth game:
https://askabiologist.asu.edu/peppered-moths-game/play.html

General resources
The always popular Populus:
https://cbs.umn.edu/populus/overview
Drift & Gene Flow 
https://cartwrig.ht/apps/genie/
(Cock van Oosterhout has a great ppt to lead students through this)
See also https://cartwrig.ht/apps/redlynx/
https://demonstrations.wolfram.com/ReplicatorMutatorDynamicsWithThreeStrategies/
NetLogo:
http://ccl.northwestern.edu/netlogo/models/index.cgi
Population Genetics:
https://www.radford.edu/~rsheehy/Gen_flash/popgen/
Evolution in general
https://evolution.berkeley.edu/evolibrary/home.php
Mitochondrial Eve:
https://projects.ncsu.edu/cals/gn/ex/mit-eve.html
Y chromosomes:
https://projects.ncsu.edu/cals/gn/ex/y-chrom.html
A professional online package from Michael Kasumovic:
https://arludo.com/
a compilation of resources:
https://planted.botany.org/index.php?P=Home
Finally, Donald Forsdyke has some great on-line videos explaining
evolutionary principles (occasionally in a fake Scottish accent):
http://post.queensu.ca/~forsdyke/videolectures.htm

The Genome 10K Project

Tue, 29 Jul 2014 09:11:04 -0500

https://genome10k.soe.ucsc.edu The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts. The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.

When Chromosomes Shift: Understanding Chromosome Rearrangement and Human Disease

BioStar — Fri, 11 Apr 2025 01:07:17 -0500

In the vast and complex world of genetics, our chromosomes are like carefully arranged bookshelves — each holding critical information that defines who we are. But what happens when those books are shuffled, inverted, or swapped? The answer lies in a phenomenon known as chromosome rearrangement, a powerful force behind many human diseases, from developmental disorders to cancer.

What Are Chromosome Rearrangements?

Chromosome rearrangements are structural changes that alter the normal configuration of chromosomes. These changes can involve large segments of DNA — from thousands to millions of base pairs — and can occur spontaneously, be inherited, or result from exposure to mutagens (like radiation or chemicals).

Common Types of Rearrangements:

Deletions – Loss of a chromosome segment
Duplications – Repetition of a segment
Inversions – A segment breaks off, flips, and reattaches
Translocations – Segments exchange places between non-homologous chromosomes
Insertions – A segment is inserted into another part of the genome

These changes can disrupt genes directly or affect gene regulation, leading to disease.

How Do Chromosome Rearrangements Cause Disease?

The impact of a rearrangement depends on which genes are involved, how much DNA is affected, and when the rearrangement occurs (in development vs. adulthood). Here are some key mechanisms:

Gene disruption: Breaking a gene can lead to loss of function or the creation of a non-functional protein.
Gene fusion: Joining parts of two genes may form a novel hybrid gene with new functions (common in cancer).
Dosage effects: Extra or missing gene copies can disturb the balance of gene expression.
Position effects: Moving a gene to a new regulatory environment may silence or over-activate it.

Chromosome Rearrangements in Human Disease

1. Developmental Disorders

Cri-du-chat syndrome: Caused by a deletion on chromosome 5p. Affected infants often have a high-pitched cry and intellectual disability.
Williams syndrome: Results from a microdeletion on chromosome 7q, affecting genes related to cardiovascular and cognitive function.

2. Cancer

Cancer is perhaps the most striking example of disease caused by chromosome rearrangements.

Chronic Myeloid Leukemia (CML): Caused by a translocation between chromosomes 9 and 22, forming the Philadelphia chromosome. This creates the BCR-ABL fusion gene, which drives uncontrolled cell growth.
Burkitt lymphoma: Involves translocation of the MYC gene, leading to excessive cell division.
Ewing sarcoma: A fusion of EWSR1 and FLI1 genes through translocation promotes tumor development.

3. Infertility and Miscarriages

Balanced rearrangements (like inversions or translocations) in carriers may not cause disease directly but can result in:

Recurrent miscarriages
Infertility
Birth defects in offspring

Detecting Rearrangements

Thanks to modern genomics, chromosome rearrangements can now be detected with high precision using:

Karyotyping – Classic method for detecting large rearrangements
FISH (Fluorescence In Situ Hybridization) – Uses fluorescent probes to target specific DNA sequences
Array CGH (Comparative Genomic Hybridization) – Detects copy number changes across the genome
Whole Genome Sequencing (WGS) – Identifies even small or complex rearrangements at base-pair resolution

Looking Forward: The Future of Chromosome Medicine

Understanding chromosome rearrangements is now central to:

Personalized medicine
Genetic counseling
Targeted therapies, especially in cancer (e.g., tyrosine kinase inhibitors for BCR-ABL fusion)

With the rise of long-read sequencing and single-cell genomics, even previously “invisible” rearrangements are being uncovered, offering new insights into both rare diseases and common conditions.

Final Thoughts

Chromosome rearrangements remind us that genetics isn't just about which genes we have — but where they are, how they're arranged, and when they're active. As our tools grow sharper, so does our ability to diagnose, understand, and treat diseases rooted in genomic architecture.

In a way, the genome is like a book not just defined by its words, but also by how the chapters are ordered. Rearranging them can create a new story — sometimes harmful, sometimes insightful — and understanding these changes is key to writing a healthier future.

Research Associate at Indian Institute of Chemical Technology (IICT), Hyderabad

Thu, 07 Aug 2014 01:55:21 -0500

Indian Institute of Chemical Technology (IICT), Hyderabad, a constituent of CSIR is a leading research Institute in the area of chemical sciences. The core strength of IICT lies in Organic Chemistry, and it continues to excel in this field for over six decades. The research efforts during these years have resulted in the development of several innovative processes for a variety of products necessary for human welfare such as drugs, agrochemicals, food, organic intermediates, adhesives etc. More than 150 technologies developed by IICT are now in commercial production.

CSIR-IICT is conducting Walk in Interview for the following position on a purely temporary basis for the sponsored project "GENESIS (BSC-0121) at 10.00 AM on 19th August 2014 at IICT, Hyderabad

Position : Research Associate
No of Post : One
Desired Profile : PhD in computation biology or M.Tech in Computational Biology with three years experience in relevant subject and atleast one research paper in SCI journal

Experience : Knowledge in vector and vector borne disease, disease modeling, GIS mapping and modeling.
Age : 35 years
Stipend : Rs 22000/- + HRA

Eligible candidate may download the application form from our website http://www.iictindia.org and appear for interview along with the duly filled in application form supported by bio-data and one set of attested photo copies of certificates of educational qualification, age, experience, caste, latest photograph and the cadndidates are required to bring all the original certificates for verification

Walk in Interview : 19.08.14

The Centre for Bioinformatics (MCB) Lab

Sun, 14 Jul 2013 12:41:20 -0500

The Centre for Bioinformatics (MCB) is a diverse collection of professors, postdoctoral fellows, and students, who share a common interest in Bioinformatics.

Research Area

We are interested in the development of the statistics and computational methods for the analysis of this data in breast cancer.
We have worked on probabilistic models for subcellular localization, protein-protein interactions, and problems related to chemical genomics.
We are interested in the development of bioinformatics/biostatistical methodology in the analysis of epigenetic/epigenomic data.
We are interested in integrative bioinformatics approaches to learn the gene, gene products, interactions, and regulatory mechanisms involved in mental retardation.

Link @ http://www.mcgill.ca/mcb/

BioProgramming

Jitendra Narayan — Sun, 14 Jul 2013 16:29:53 -0500

The completion of the first human genome drafts was just a start of the modern DNA sequencing era which resulted in further invention, improved development toward new advanced strategies of high-throughput DNA sequencing, so called the “high-throughput next generation sequencing” (HT-NGS). The decreasing genome sequencing cost and desire to explore and understand biological machanism at genomic level, speed up the genomic sequencing projects. In the fast growing HT-NGS technologies, the main challenge is to cope with the analysis of vast production of sequencing database through advanced bioinformatics tools. In oder to develope sotware/tools bioinformatician/ biological programmers need to expertise in any one one the programming language. However, sometime one language are not enough to handle all sort of biological needs, which compel us to learn new biologically suitable language to handle ever growing genome or protein sequences.

The next step after reading genetic code is writing a script to analyse and explore the hidden information. This tutorial is aimed to introduce you new biological programming languages with their packages/libraries, and assist in your scripting work.

Navigate the sub-section of this page [ see right hand side of the page for it ]

Project Fellow at Institute of Himalayan Bioresource Technology

Fri, 15 Aug 2014 06:50:08 -0500

Research Associate/ Project FellowDate of posting:14 Aug

Eligibility : MSc, M Phil / Phd, BE/B.Tech
Location : Himachal Pradesh-other
Job Category : Govt Jobs, Research, Walkin
Last Date : 20 Aug 2014

Advertisement No.6/2014

Post : Project Fellow
Research Associate/ Project Fellow Jobs opportunity in CSIR-Institute of Himalayan Bioresource Technology
M.Sc. in Bioinformatics/Computer Science with 55% marks and (ii) M.Sc. Bioinformatics/ Computational biology/ P.G. Diploma in Bioinformatics/B.Tech. or higher Degree in Bioinformatics with 55% marks

Date of Interview: 29.08.2014.

More at http://www.ihbt.res.in/recruit/AdvtNo6_2014.pdf