Literature DB >> 35674906

Bioinformatics Tools to Understand Notch.

Ashley Avila1, Roxana Gonzalez Tascon1, Dongyu Jia2.   

Abstract

As a result of the culmination of data, and the fast-paced advancement of new research, all the biological information collected can make it difficult to sort data. This is oftentimes experienced when learning about the human genome. Fortunately, with the advancement of technology, the field of bioinformatics has emerged which has allowed for the creation of a variety of biological databases. These biological databases provide a condensed reservoir of organized information that is easy to use and topic-specific. Here, we provide a list of 39 biological databases that help break down the fundamental details of a gene. This chapter uses the NOTCH1 gene as an example to demonstrate how biological databases can be used to extract gene information. Five sections were created to highlight the major areas needed to build a comprehensive foundation of NOTCH1. The first section lists databases containing basic gene and protein product information. The next section consists of protein interactions and signaling pathway databases which are essential in understanding the biological processes a gene product is involved in. Gene expression and disease databases are the next two sections which are connected since disease results from the aberrant expression of a gene product. The last database section examines model organisms which serve a key role in the study of human genetic diseases. Using these databases, we can elucidate NOTCH1's gene/protein structure, expression, and vital physiological function through the Notch signaling pathway.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Bioinformatics tools; Notch signaling

Mesh:

Year:  2022        PMID: 35674906     DOI: 10.1007/978-1-0716-2201-8_20

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  8 in total

Review 1.  Notch signaling at a glance.

Authors:  Kazuya Hori; Anindya Sen; Spyros Artavanis-Tsakonas
Journal:  J Cell Sci       Date:  2013-05-31       Impact factor: 5.285

Review 2.  UCSC genome browser tutorial.

Authors:  Ann S Zweig; Donna Karolchik; Robert M Kuhn; David Haussler; W James Kent
Journal:  Genomics       Date:  2008-06-02       Impact factor: 5.736

3.  A COL11A1-correlated pan-cancer gene signature of activated fibroblasts for the prioritization of therapeutic targets.

Authors:  Dongyu Jia; Zhenqiu Liu; Nan Deng; Tuan Zea Tan; Ruby Yun-Ju Huang; Barbie Taylor-Harding; Dong-Joo Cheon; Kate Lawrenson; Wolf R Wiedemeyer; Ann E Walts; Beth Y Karlan; Sandra Orsulic
Journal:  Cancer Lett       Date:  2016-09-05       Impact factor: 8.679

Review 4.  Targeting Notch signaling pathway to overcome drug resistance for cancer therapy.

Authors:  Zhiwei Wang; Yiwei Li; Aamir Ahmad; Asfar S Azmi; Sanjeev Banerjee; Dejuan Kong; Fazlul H Sarkar
Journal:  Biochim Biophys Acta       Date:  2010-06-22

Review 5.  The Varied Roles of Notch in Cancer.

Authors:  Jon C Aster; Warren S Pear; Stephen C Blacklow
Journal:  Annu Rev Pathol       Date:  2016-12-05       Impact factor: 23.472

6.  Notch signaling genes: myogenic DNA hypomethylation and 5-hydroxymethylcytosine.

Authors:  Jolyon Terragni; Guoqiang Zhang; Zhiyi Sun; Sriharsa Pradhan; Lingyun Song; Gregory E Crawford; Michelle Lacey; Melanie Ehrlich
Journal:  Epigenetics       Date:  2014-03-26       Impact factor: 4.528

7.  DNA topoisomerase IIα and RAD21 cohesin complex component are predicted as potential therapeutic targets in bladder cancer.

Authors:  Zhiling Yu; Qiuping Xu; Guixue Wang; Molly Rowe; Cameron Driskell; Qian Xie; Minhong Wu; Dongyu Jia
Journal:  Oncol Lett       Date:  2019-05-17       Impact factor: 2.967

8.  Highly accurate protein structure prediction with AlphaFold.

Authors:  John Jumper; Richard Evans; Alexander Pritzel; Tim Green; Michael Figurnov; Olaf Ronneberger; Kathryn Tunyasuvunakool; Russ Bates; Augustin Žídek; Anna Potapenko; Alex Bridgland; Clemens Meyer; Simon A A Kohl; Andrew J Ballard; Andrew Cowie; Bernardino Romera-Paredes; Stanislav Nikolov; Rishub Jain; Demis Hassabis; Jonas Adler; Trevor Back; Stig Petersen; David Reiman; Ellen Clancy; Michal Zielinski; Martin Steinegger; Michalina Pacholska; Tamas Berghammer; Sebastian Bodenstein; David Silver; Oriol Vinyals; Andrew W Senior; Koray Kavukcuoglu; Pushmeet Kohli
Journal:  Nature       Date:  2021-07-15       Impact factor: 49.962

  8 in total

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