Bioinformatics News
This Month in Bioinformatics- Research Updates of October 2020
Some of the important findings made this month in bioinformatics are mentioned in this article.
1. Fast histone turnover and H3.3 incorporation compatibility with hallmarks of heterochromatin
A new study on nucleosome turnover demonstrates that the fast histone turnover and H3.3 incorporation is compatible with the hallmarks of heterochromatin [1]. H3.3 is a replication-independent histone variant and is considered as a hallmark of regulatory regions in the animal genome. They have found that nucleosomes are evicted by the Smarcad1 chromatin remodeler leading to the generation of accessible DNA [1]. According to this study, Smarcad1 and H3.3 play opposing roles in the dynamic heterochromatin state in embryonic stem cells in mice. For more information, read here.
2. A new suite for PacBio Sequel raw sequence data analysis
A new suite of tools called SequelTools has been developed for analyzing PacBio raw sequence data [2]. SequelTools is a command-line program that consists of tools for read subsampling, quality control, and read filtering [2]. According to the authors, there is no such tool available yet for analyzing the quality, subsampling, and filtering of PacBio raw sequence data. For more information, read here.
3. A new tool for ORFs and microproteins function prediction
A new tool called smORFunction has been developed for function prediction of small open reading frames (smORFs) and microproteins [3]. smORFunction can predict functions of smORFs or microproteins in 265 models generated from 173 datasets. These datasets include tissues/cells, diseased, and normal. Currently, it consists of 617,462 unique smORFs that are annotated by different tools SmPROT and sORFs.org. For more information, read here and here.
4. A new model for androgen receptor toxicity prediction
A new prediction model has been developed for androgen receptor activity. This method is based on 2D chemical structure images of compounds [4]. This method extracts unknown features that may be neglected by conventional numerical methods. This method was tested on datasets and reveals high accuracy including a positive predictive value (PPV) of 0.933, Mathews correlation coefficient (MCC) of 0.688, a specificity of 0.998, a sensitivity of 0.519, and overall accuracy of 0.981 in 10-fold cross-validation. For more information, read here.
5. A new tool for geneset network analysis
Python Geneset Network Analysis (PyGNA) is a new tool developed for network-aware geneset analysis. It is based on an integrated statistical framework facilitating easy integration into existing analysis pipelines. It provides high-quality images and reports. PyGNA is available as a Python package at http://github.com/stracquadaniolab/pygna. For more information, read here.
References
- Navarro, C., Lyu, J., Katsori, A. M., Caridha, R., & Elsässer, S. J. (2020). An embryonic stem cell-specific heterochromatin state promotes core histone exchange in the absence of DNA accessibility. Nature Communications, 11(1), 1-14.
- Hufnagel, D. E., Hufford, M. B., & Seetharam, A. S. (2020). SequelTools: a suite of tools for working with PacBio Sequel raw sequence data. BMC bioinformatics, 21(1), 1-11.
- Ji, X., Cui, C., & Cui, Q. (2020). smORFunction: a tool for predicting functions of small open reading frames and microproteins. BMC bioinformatics, 21(1), 1-13.
- Yu, M., Lee, J., Lee, Y. et al. (2020). 2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor. BMC Bioinformatics 21, 245.
- Fanfani, V., Cassano, F., & Stracquadanio, G. (2020). PyGNA: a unified framework for geneset network analysis. BMC bioinformatics, 21(1), 1-22.
A new study has revealed new forms of proteins that have never been seen before along with unexpected connections. Last year, Google DeepMind predicted the structure of all known proteins from organisms using AlphaFold [1].
MANE is a collaborative project between NCBI and EMBL-EBI. It stands for Matched Annotation from NCBI and EMBL-EBI [1]. The datasets provided by NCBI and EMBL-EBI on the human genome are not identical across every gene.
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We are going to lead a few bioinformatics research projects. For that, we are creating a new research group of Bioinformatics Review. (more…)
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Bioinformatics Review compiles a list of top bioinformaticians every two years. We are inviting nominations for the second edition of this award after the 2018 List. We invite you to contribute to this endeavor by nominating your colleague or friends if you think they can make it to our list.
Nominations start from 20th June 2020 till 15th August 2020. All the nominees will be informed via email on 5th September 2020. We use a well-established ranking method called ScipRank. Our data collection is open-source. ScipRank methodology is publicly available for scrutiny.
Also, we are completing 5th year of success in Bioinformatics Review this year. On this occasion, we are organizing an International Conference on Advanced Research in Bioinformatics 2020. The award will be declared at the conclusion of ConARB 2020 – 3 & 4th Oct 2020).
We invite you to contribute to this endeavor by nominating your colleague or friends. You can also submit your papers, which if accepted, can be presented at the conference.
We have set up a dedicated portal for ConARB 2020 accessible here https://conarb.
To attend or to submit your abstract or to nominate someone, kindly visit this website. Accepted papers will be published in a special issue of Bioinformatics Review.
Department of Biotechnology (DBT), India is organizing a 5-day workshop on “CRISPR/Cas mediated genome editing in plants: Applications, tools, and experimental design” to address the strategies and methods involved in genome modification utilized as essential tools in research and development. (more…)
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