We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.

For detailed instructions, please refer to the panHiTE tutorial.

Address of the bookmark: https://github.com/CSU-KangHu/HiTE

“It’s like a subway map,” she said, “but for DNA.”

That idea is exactly what Sequence Tube Map brings to life.

Instead of showing a genome as one long, confusing sequence, it displays different genomic paths like routes on a metro map. Where sequences are shared, the paths travel together. Where genetic variation occurs, they branch into different routes and may join again later.

This makes complex genome graphs much easier to explore.

Maya could now see how different haplotypes moved through the same genomic region and where they took different paths. She could even view sequencing reads mapped onto the graph, helping her understand what was happening in regions with genetic variation.

What once looked like a tangled network now looked like a journey.

Sequence Tube Map turns the complexity of graph genomes into a visual story—making it easier for scientists to see how DNA can take different routes.

Read more at  https://github.com/vgteam/sequencetubemap 

and

https://academic.oup.com/bioinformatics/article/35/24/5318/5542397

Demo at https://vgteam.github.io/sequenceTubeMap/

Instead of asking only whether two genes occur together across genomes, CORGIAS asks a deeper question: did these genes actually evolve together, repeatedly gaining or losing their presence in concert, or are they merely travelling together because of their inherited history? The framework introduces two complementary approaches, Ancestral State Adjustment (ASA) and the Simultaneous EVolution test (SEV), which incorporate evolutionary information into the search for gene associations. This distinction becomes increasingly important as genome sequencing continues to uncover enormous numbers of microbial genomes, many from organisms that have never been cultured and whose genes remain functionally mysterious. In this growing genomic landscape, simply finding a gene is no longer enough—we need clues about what that gene might be doing. CORGIAS approaches this problem almost like a genomic detective: rather than treating every association as evidence, it reconstructs the evolutionary story behind the association and asks whether the evidence survives that history. By doing so, it offers a way to separate coincidence from biological connection and potentially uncover functional relationships hidden within the vast microbial genomic landscape. The broader message is beautifully simple: genes do not evolve in isolation, and understanding what they do may require us to look beyond where they are today and reconstruct how they arrived there. Sometimes, the most important clue in a genome is not the gene itself, but the evolutionary journey it has taken.

More at https://academic.oup.com/nargab/article/7/4/lqaf182/8377910?

It installs in any computer even if you don't have administrator rights!

Address of the bookmark: http://www.dnabaser.com/download/DNA-Counter/index.html

Address of the bookmark: https://github.com/olarerin/metaPlotR

RNAs, especially non-coding RNAs (such as microRNA, long ncRNAs) are recently identified to be very abundant in mammalian organisms and play some key roles in gene expression regulation, gene silencing, and also implicated in disease progression, stem cell pluripotency etc. Current research activities of our lab include analysis of expression pattern of ncRNAs by microarray and next-gen sequencing data and understanding the role of miRNAs or other regulatory RNAs in various diseases, especially cancer and validation by reporter assays (renilla/luciferase) and other experimental tools.

More @ http://vvekslab.in/index.html

https://www.pmgenomics.ca/hoffmanlab/

In this project, you will use single-molecule techniques to label mRNA and DNA in (live and fixed) Drosophila embryos and fixed embryonic bodies. You will also use super-resolution microscopy to visualize protein condensates. Co-localization dynamics reflecting DNA-protein bindings and DNA looping events will be detected, analyzed, and used to test computational models of gene transcription.

Qualification:
MSc degree (or equivalent) in Biology, Biophysics, or Bioengineering

Experience in one or more of these areas: (1) molecular cloning, (2) imaging, (3) image analysis (using Matlab/Python/Java), (4) microfluidics, and (5) computational modeling.

How to Apply?
Send (1) your CV, (2) summary of research experience, and (3) email addresses of at least 2 references to ezzat.el-sherif@fau.de. Title your email ‘Transcription PhD Position’.

salary Grade.: E13
Total Time: 3 Jahre
Start: 01.01.2020.
End: 31.3.2020.

Address:
Dr. El-Sherif, Ezzat
Department Biologie
Professur für Zoologie (Entwicklungsbiologie) (Prof. Dr. Klingler)
Telefon 09131/85-28068, Fax 09131/85-28040, E-Mail: ezzat.el-sherif@fau.de

Protein-protein and protein-DNA/RNA docking based on a hybrid algorithm of template-based modeling and ab initio free docking.

The HDOCK server distinguishes itself from similar docking servers in its ability to support amino acid sequences as input and a hybrid docking strategy in which experimental information about the protein–protein binding site and small-angle X-ray scattering can be incorporated during the docking and post-docking processes.

Address of the bookmark: http://hdock.phys.hust.edu.cn/