https://www.bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html

Address of the bookmark: https://github.com/PoisonAlien/maftools

NAME OF THE POST : SRF/JRF (Four Posts only)

DURATION : Indicated with the respective project mentioned below:

NAME OF THE PROJECT : As Mentioned below:

1. Serological diversity and molecular characterization of Dichelobector nodusus and development of vaccine against virulent footroot funded by NAIP. (Tenable upto 31.03.2014)

2. Development of oral vaccine against Clostridium perfringenes employing translational fusion of immunodominant epitopes of beta toxin with heat labile entertoxin B funded by DBT. (Tenable upto 25.02.2014)

3. Indo-Norwegian project, “Evaluation of major porins, ompC and ompR of Areomonas hydrophila as potential vaccine candidates and identification and characterization of immune genes of Indian major carp, Labeo rohita” (Tenable upto 31.03.2014)

EDUCATIONAL QUALIFICATIONS: For JRF- M.Sc/M.Tech in any subject of Biological Sciences/Life Sciences

For SRF- M.Sc/M.Tech in any subject of Biological Sciences/Life Sciences with 2 years of Research Experience.

JOB DESCRIPTION : The Candidate should have experience in gene Expression, protein purification, molecular biology techniques and bioinformatics
EMOLUMENTS : SRF: Rs. 18,000/- per month consolidated plus 30% HRA if /NET/GATE qualified otherwise Rs. 14,000/- per month consolidated + 30% HRA.

JRF: Rs. 16,000/- per month consolidated + 30% HRA if NET/GATE qualified otherwise Rs. 12,000/- per month consolidated + 30% HRA

SCIENTIST NAME : Dr. Lalit C. Garg, SS-VII (Gene Regulation Lab)

SCIENTIST’S EMAIL : lalit@nii.ac.in

WALK IN INTERVIEW ON : October 31st, 2013

REGISTRATION OF CANDIDATES: 10.30 AM to 11.00 AM

Advertisement: http://www1.nii.res.in/sites/default/files/project-Dr.Lalit-31oct2013.pdf

USAGE:

• -query: sequence A in fasta format
• -db: sequence B in fasta format
• -out: output matrix
• -kmer Integer: k>1 (default 32) Use 32 for chromosomes and genomes and 16 for small bacteria
• -diffuse Integer: z>0 (default 4) Use 4 for everything - if using large plant genomes you can try using 1
• -dimension Size of the output matrix and plot. Integer: d>0 (default 1000) Use 1000 for everything that is not full genome size, where 2000 is recommended

Address of the bookmark: https://github.com/estebanpw/chromeister

More at http://incob2014.org/

Address of the bookmark: https://www.science.org/doi/10.1126/science.abj6987

There are several jobs opening in bioinformatics all around the world, but many of them do not get proper attention due to lack of advertisements, or social connectivity. This bookmark is created for an academic, non-academic, scientists and budding researchers to help and updates the bioinformatics/computational biology jobs links of all know websites around the world.

I also love to stream the live bioinformatics or Computational biology jobs updates using Twitter https://twitter.com/search?q=bioinformatics%20jobs&src=typd

Find out here about exciting job opportunities in the life sciences.

Please add well known bioinformatics jobs websites below in comment section.

Address of the bookmark: http://www.nature.com/naturejobs/science/jobs?utf8=%E2%9C%93&q=bioinformatics&where=&commit=Find+Jobs

Address of the bookmark: https://github.com/GMOD/jb2profile

Lab page @ http://www.mathomics.cl/

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:

1. Deletions – Loss of a chromosome segment

2. Duplications – Repetition of a segment

3. Inversions – A segment breaks off, flips, and reattaches

4. Translocations – Segments exchange places between non-homologous chromosomes

5. 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.

At the Repository for Tomato Genomics Resources, we are working on Tomato Functional Genomics, using TILLING, Insertional Mutagenesis, proteomics, metabolomics approaches to study fruit ripening in tomato. The current aims of the group include using reverse and forward genetics strategies to isolate tomato mutants delayed in ripening, having high lycopene and folate content in tomato fruits and analysis of light and hormonal signal transduction pathways. For recent publications of the group see (Plant Physiol 161: 2085–2101, Plant Physiol 156: 1424-1438; Molecular Plant 3: 854-869; Plant Methods 6: 3; Plant Methods 5:18; Plant Signaling and Behavior 5:11.).

Currently we have one position available in the projects awarded to Prof. R.P. Sharma funded by Dept of Biotechnology. The qualification for this Position is as follows:

Research Assistant: Applicants should have experience in networking using R language and should be able to develop networks using the transcriptome, proteome and metabolite data sets. M.Tech. in Bioinformatics is required. The selected candidate would be paid Rs. 13,000/-pm- consolidated.

Candidates interested in above positions should send a one page statement clearly explaining how their skills are relevant to the position. The candidates should also enclose detailed CV and the name/email id for three referees. The candidates can send their application by email at rameshwar.sharma@uohyd.ac.in and y.sreelakshmi@uohyd.ac.in on or before December 10th, 2013. The position is purely temporary in nature. Shortlisted candidates would be called for interview. No TA/DA would be provided for attending the interview. We also have openings for CSIR-NET JRF candidates for pursuing PhD in above research areas.

Interested candidates with CSIR-NET JRF can send their CV to the above email
addresses.

Advertisement:

http://www.uohyd.ac.in/images/recruitment/tomanet_positions_221113.pdf