Address of the bookmark: https://github.com/lh3/psmc

MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to $5 per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.

In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for $1 million.

The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.

Powered by DNBseq™, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.

SOURCE MGI

https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/

http://en.mgitech.cn/

Address of the bookmark: https://github.com/google/nucleus

Breeding Insight is funded by the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) through Cornell University. The USDA ARS delivers scientific solutions to national and global agricultural challenges. As a global leader in agricultural discovery through scientific excellence, ARS is committed to delivering cutting-edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well-being of all people; sustaining our nation’s agroecosystems and natural resources; and ensuring the economic competitiveness and excellence of our agriculture.

Address of the bookmark: https://www.breedinginsight.org/

More at https://pubmed.ncbi.nlm.nih.gov/34951622/

Address of the bookmark: https://github.com/EbmeyerSt/GEnView

In this post, we’ll explore the core methods used in comparative genomics, the questions they help answer, and how they’re shaping our understanding of life.

1. Whole-Genome Alignment
Whole-genome alignment involves mapping the entire genome of one species to another. Tools like MUMmer, MAUVE, and LASTZ perform large-scale sequence alignments to detect conserved regions, rearrangements, insertions, and deletions.

Use Case:
Comparing human and chimpanzee genomes to identify evolutionary conserved sequences (ECS) and regions of divergence.

Key Challenges:
Handling repetitive sequences and genome rearrangements.

Computational complexity in large genomes.

2. Synteny and Collinearity Analysis
Synteny refers to conserved blocks of gene order across species. Tools like MCScanX, SynMap, or CHITRA (for visualizing synteny interactively) detect these blocks to understand chromosomal evolution.

Use Case:
Studying ancient genome duplications in plants.

Investigating chromosomal rearrangements in cancer genomes.

3. Ortholog and Paralog Detection
Orthologs are genes in different species that evolved from a common ancestor, while paralogs are genes duplicated within a genome. Identifying them is crucial for functional annotation and evolutionary studies.

Popular Tools:
OrthoFinder, Orthologous MAtrix (OMA), InParanoid, and EggNOG.

Use Case:
Functional prediction of uncharacterized genes based on orthologs in model organisms.

Tracing gene family evolution.

4. Phylogenomic Analysis
Phylogenomic methods combine phylogenetics and genomics to infer evolutionary trees based on genome-wide data. These methods can handle dozens to hundreds of genomes, using concatenated alignments or gene trees.

Tools:
RAxML, IQ-TREE, ASTRAL, Phylip, BEAST.

Use Case:
Resolving the evolutionary relationships between microbial species.

Studying speciation events.

5. Pan-Genome Analysis
The pan-genome consists of the core genome (shared by all strains) and the accessory genome (strain-specific genes). This is especially popular in microbial genomics.

Tools:
Roary, Panaroo, BPGA, PGAP.

Use Case:
Understanding virulence factor diversity in E. coli.

Designing broad-spectrum vaccines.

6. Comparative Transcriptomics
Comparing transcriptomes across species or conditions reveals conserved and unique expression patterns. RNA-seq data can be mapped to reference genomes to identify orthologous expression profiles.

Use Case:
Comparing stress response in extremophiles and model species.

Studying conserved regulatory networks.

7. Functional Element Comparison
Beyond genes, comparative genomics also targets non-coding regions—enhancers, promoters, miRNAs. Conservation across species often implies functional importance.

Tools:
PhastCons, GERP, phyloP (based on multiple alignments).

Use Case:
Detecting conserved non-coding elements in vertebrates.

Studying regulatory divergence in human evolution.

8. Horizontal Gene Transfer (HGT) Detection
In microbes, genes often jump across species boundaries. Comparative genomics can detect HGT by identifying genes that defy the expected phylogenetic pattern.

Tools:
HGTector, DarkHorse, AlienHunter, SIGI-HMM.

Use Case:
Tracing antibiotic resistance genes.

Exploring microbial adaptability in extreme environments.

Final Thoughts
Comparative genomics is a powerful lens to observe the diversity and unity of life. With a broad toolkit—from aligners to orthology pipelines, phylogenetic engines to visualization tools—it allows scientists to ask big questions: How did genomes evolve? What makes species unique? Where do new genes come from?

Whether you're studying extremophiles, building better crops, or exploring human ancestry, comparative genomics offers the methods to connect the dots across the tree of life.

Bachelor/ BS Bioinformatics at
1. Al-khair University, Bhimber
2. Government College University, Faisalabad
3. University Of Agriculture, Faisalabad
4. Comsats Institute Of Information Technology [isb], Islamabad
5. International Islamic University, Islamabad
6. Quaid-e-azam University, Islamabad
7. Khushal Khan Khattak University, Karak
8. Virtual University Of Pakistan, Lahore
9. Virtual University Of Pakistan, Lahore
10. Hazara University, Mansehra
11. Shaheed Benazir Bhutto Women University, Peshawar
12. Comsats Institute Of Information Technology, Sahiwal
13. Capital University Of Science And Technology, Islamabad
14. Foundation University, Islamabad
15. Baqai Medical University/hospital, Karachi
16. Institute Of Business And Technology(main Campus), Karachi
17. Sir Syed University Of Engineering & Technology, Karachi
18. Forman Christian College, Lahore
19. Qarshi University (lhr), Lahore
20. The Superior University, Lahore
21. University Of Management And Technology, Lahore
22. Federal Institute Of Health Sciences, Lahore
23. Shaheed Benazir Bhutto Women University Peshawar, Sub Campus, Swabi
24. Government Postgraduate College ( Mandian), Abbottabad
25. Federal Institute Of Health Sciences, Multan
26. Fedral Institute Of Health Sciences, Muzaffarabad
27. The Limit Institution Of Health Sciences, Sahiwal

Master/ MS Bioinformatics cources at
1. Government College University, Faisalabad
2. Comsats Institute Of Information Technology [isb], Islamabad
3. International Islamic University, Islamabad
4. National University Of Science & Technology, Islamabad
5. Quaid-e-azam University, Islamabad
6. University Of Sindh, Jamshoro
7. Virtual University Of Pakistan, Lahore
8. Hazara University, Mansehra
9. Shaheed Benazir Bhutto Women University, Peshawar
10. Capital University Of Science And Technology, Islamabad
11. Cecos University Of Information Tech. & Emerging Sciences, Peshawar

The real bioinformatics scope lies if there are research labs which work in this field. One has to take account of that. If so then try to get information of those labs and visit them to get a hang of the work they pursue.

There is a huge buzz of precision medicine in light of genomics all around the world. One should also try to see how genomics infrastructure is built up or standing in Pakistan. If research labs having collaboration with hospitals employ genomics then one must also visit such labs. This will bring new avenues in healthcare advances. Not only it opens up the wealth of knowledge one can make out of genomics study but will also advance the critical thinking of therapies.

So I would encourage to target research labs working in the fields and also get information of hospitals employing genomics, this will give you an overall understanding of the fields demand in your country.

Bioinformatics is full of opportunities. The sector is poised to open new avenues for the other related sectors also. But the biggest opportunity area in the Bioinformatics market will be in the drug discovery sector. Reduction of both the cost and time taken to discover a new drug due to fast development in the Bioinformatics tools and software zone is also making drug discovery an attractive field to venture in. Malaysian bioinformatics growth and future are discuss in this https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723929/ paper. Keeping all such inportance in mind, following universities in Malaysia offering bioinformatics cources:

3 program(s) at AIMST University, Malaysia

Master of Science in Biotechnology (MSc) - Bioinformatics by Research

Master of Science (M.Sc) in Medical Microbiology (Bioinformatics) by Research

Doctor of Philosophy in Biotechnology (PhD) - Bioinformatics by Research

1 program(s) at INTI International University and Colleges, Malaysia

American Degree Transfer Program (Biosciences) in Bioinformatics

3 program(s) at Management and Science University (MSU), Malaysia

Master in Bioinformatics (By Research)

PhD in Bioinformatics

Bachelor in Bioinformatics (Hons)

1 program(s) at Multimedia University (MMU), Malaysia

Bachelor of Science (Honours) Bioinformatics

1 program(s) at Universiti Industri Selangor (UNISEL) Bestari Jaya Campus, Malaysia

Bachelor of Bioinformatics (Hons)

2 program(s) at Universiti Malaysia Sabah (UMS), Malaysia

PhD - Doctor of Philosophy in Bioinformatics (By Research)

MSc - Master of Science in Bioinformatics (By Research)

6 program(s) at Universiti Putra Malaysia (UPM), Malaysia

MSc - Master of Science in Bioinformatics by Research

Master of Science in Bioinformatics and System Biology by Research

Master of Science (M.Sc) in Bioinformatics and Systems Biology (With Thesis)

PhD - Doctor of Philosophy in Bioinformatics by Research

PhD - Doctor of Philosophy in Bioinformatics and Systems Biology (With Thesis)

PhD - Doctor of Philosophy in Bioinformatics and System Biology by Research

1 program(s) at Universiti Selangor (UNISEL), Malaysia

Bachelor of Bioinformatics (Hons)

3 program(s) at Universiti Teknologi Malaysia (UTM), Malaysia

M.Sc - Master of Science (Bioscience) in Bioinformatics Research Group (BIRG) By Research

PhD - Doctor of Philosophy (Bioscience) in Bioinformatics Research Group (BIRG) By Research

Bachelor of Computer Science (BioInformatics)

4 program(s) at University of Malaya (UM), Malaysia

MSc - Master of Science in Bioinformatics by Research

Master in Bioinformatics by Coursework

PhD - Doctor of Philosophy in Bioinformatics by Research

Bachelor of Science (BSc) in Bioinformatics

3 program(s) at Perdana University, Malaysia

Master in Bioinformatics (By Research)

PhD in Bioinformatics

Bachelor in Bioinformatics (Hons)

3 program(s) at Monash University, Malaysia

Master in Bioinformatics (By Research)

PhD in Bioinformatics

Bachelor in Bioinformatics (Hons)

The real bioinformatics scope lies if there are research labs which work in this field. One has to take account of that. If so then try to get information of those labs and visit them to get a hang of the work they pursue. For detail Bioinformatics in Malaysia: Hope, Initiative, Effort, Reality, and Challenges are discussed in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723929/ paper.

Candidates desirous of doing a short-term training / final year dissertation project for MSc (Life Sciences/Bioinformatics/Biotechnology or any science discipline) at UIAR Biophysics and Bioinformatics department may please drop an email atanju@iiar.res.in along with their resume.

Selected candidates will be further intimated. There will be a fees charged for doing the project at UIAR. The projects will be experimental or computational or involve both.

The training scope will be in the following areas but not limited to:

Bioinformatics analysis, Docking and Virtual screening, Molecular Dynamics simulation, Cloning, expression and purification of proteins, Biophysical and Biochemical characterisation of proteins, Crystallization and Structural Studies.

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CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&A sessions are added advantages of this workshop.

Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.

Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.