• Title/Summary/Keyword: Computational Biology

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Kinetic Analysis of the MAPK and PI3K/Akt Signaling Pathways

  • Suresh, Babu CV;Babar, Sheikh Md. Enayetul;Song, Eun Joo;Oh, Eulsik;Yoo, Young Sook
    • Molecules and Cells
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    • v.25 no.3
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    • pp.397-406
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    • 2008
  • Computational modeling of signal transduction is currently attracting much attention as it can promote the understanding of complex signal transduction mechanisms. Although several mathematical models have been used to examine signaling pathways, little attention has been given to crosstalk mechanisms. In this study, an attempt was made to develop a computational model for the pathways involving growth-factor-mediated mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3'-kinase/protein kinase B (PI3K/Akt). In addition, the dynamics of the protein activities were analyzed based on a set of kinetic data. The simulation approach integrates the information on several levels and predicts systems behavior. The in-silico analysis conducted revealed that the Raf and Akt pathways act independently.

Phytocompounds from T. conoides identified for targeting JNK2 protein in breast cancer

  • Sruthy, Sathish;Thirumurthy, Madhavan
    • Journal of Integrative Natural Science
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    • v.15 no.4
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    • pp.153-161
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    • 2022
  • c-Jun N-terminal kinases (JNKs) are members of MAPK family. Many genes can relay signals that promote inflammation, cell proliferation, or cell death which causes several diseases have been associated to mutations in the JNK gene family. The JNK2 gene is significantly more important in cancer development than the JNK1 and JNK3 genes. There are several different ways in which JNK2 contributes to breast cancer, and one of these is through its role in cell migration. As a result, this study's primary objective was to employ computational strategies to identify promising leads that potentially target the JNK2 protein in a strategy to alleviate breast cancer. We have derived these anticancer compounds from marine brown seaweed called Turbinaria conoides. We have identified compounds Ethane, 1, 1-diethoxy- and Butane, 2-ethoxy as promising anti-cancer drugs by molecular docking, DFT, and ADME study.

Metagenome-Assembled Genomes of Komagataeibacter from Kombucha Exposed to Mars-Like Conditions Reveal the Secrets in Tolerating Extraterrestrial Stresses

  • Lee, Imchang;Podolich, Olga;Brenig, Bertram;Tiwari, Sandeep;Azevedo, Vasco;de Carvalho, Daniel Santana;Uetanabaro, Ana Paula Trovatti;Goes-Neto, Aristoteles;Alzahrani, Khalid J.;Reva, Oleg;Kozyrovska, Natalia;de Vera, Jean-Pierre;Barh, Debmalya;Kim, Bong-Soo
    • Journal of Microbiology and Biotechnology
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    • v.32 no.8
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    • pp.967-975
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    • 2022
  • Kombucha mutualistic community (KMC) is composed by acetic acid bacteria and yeasts, producing fermented tea with health benefits. As part of the BIOlogy and Mars EXperiment (BIOMEX) project, the effect of Mars-like conditions on the KMC was analyzed. Here, we analyzed metagenome-assembled genomes (MAGs) of the Komagataeibacter, which is a predominant genus in KMC, to understand their roles in the KMC after exposure to Mars-like conditions (outside the International Space Station) based on functional genetic elements. We constructed three MAGs: K. hansenii, K. rhaeticus, and K. oboediens. Our results showed that (i) K. oboediens MAG functionally more complex than K. hansenii, (ii) K. hansenii is a keystone in KMCs with specific functional features to tolerate extreme stress, and (iii) genes related to the PPDK, betaine biosynthesis, polyamines biosynthesis, sulfate-sulfur assimilation pathway as well as type II toxin-antitoxin (TA) system, quorum sensing (QS) system, and cellulose production could play important roles in the resilience of KMC after exposure to Mars-like stress. Our findings show the potential mechanisms through which Komagataeibacter tolerates the extraterrestrial stress and will help to understand minimal microbial composition of KMC for space travelers.

Next-Generation Sequencing and Epigenomics Research: A Hammer in Search of Nails

  • Sarda, Shrutii;Hannenhalli, Sridhar
    • Genomics & Informatics
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    • v.12 no.1
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    • pp.2-11
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    • 2014
  • After the initial enthusiasm of the human genome project, it became clear that without additional data pertaining to the epigenome, i.e., how the genome is marked at specific developmental periods, in different tissues, as well as across individuals and species-the promise of the genome sequencing project in understanding biology cannot be fulfilled. This realization prompted several large-scale efforts to map the epigenome, most notably the Encyclopedia of DNA Elements (ENCODE) project. While there is essentially a single genome in an individual, there are hundreds of epigenomes, corresponding to various types of epigenomic marks at different developmental times and in multiple tissue types. Unprecedented advances in next-generation sequencing (NGS) technologies, by virtue of low cost and high speeds that continue to improve at a rate beyond what is anticipated by Moore's law for computer hardware technologies, have revolutionized molecular biology and genetics research, and have in turn prompted innovative ways to reduce the problem of measuring cellular events involving DNA or RNA into a sequencing problem. In this article, we provide a brief overview of the epigenome, the various types of epigenomic data afforded by NGS, and some of the novel discoveries yielded by the epigenomics projects. We also provide ample references for the reader to get in-depth information on these topics.

The future of bioinformntics

  • Gribskov, Michael
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2003.10a
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    • pp.1-1
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    • 2003
  • It is clear that computers will play a key role in the biology of the future. Even now, it is virtually impossible to keep track of the key proteins, their names and associated gene names, physical constants(e.g. binding constants, reaction constants, etc.), and hewn physical and genetic interactions without computational assistance. In this sense, computers act as an auxiliary brain, allowing one to keep track of thousands of complex molecules and their interactions. With the advent of gene expression array technology, many experiments are simply impossible without this computer assistance. In the future, as we seek to integrate the reductionist description of life provided by genomic sequencing into complex and sophisticated models of living systems, computers will play an increasingly important role in both analyzing data and generating experimentally testable hypotheses. The future of bioinformatics is thus being driven by potent technological and scientific forces. On the technological side, new experimental technologies such as microarrays, protein arrays, high-throughput expression and three-dimensional structure determination prove rapidly increasing amounts of detailed experimental information on a genomic scale. On the computational side, faster computers, ubiquitous computing systems, high-speed networks provide a powerful but rapidly changing environment of potentially immense power. The challenges we face are enormous: How do we create stable data resources when both the science and computational technology change rapidly? How do integrate and synthesize information from many disparate subdisciplines, each with their own vocabulary and viewpoint? How do we 'liberate' the scientific literature so that it can be incorporated into electronic resources? How do we take advantage of advances in computing and networking to build the international infrastructure needed to support a complete understanding of biological systems. The seeds to the solutions of these problems exist, at least partially, today. These solutions emphasize ubiquitous high-speed computation, database interoperation, federation, and integration, and the development of research networks that capture scientific knowledge rather than just the ABCs of genomic sequence. 1 will discuss a number of these solutions, with examples from existing resources, as well as area where solutions do not currently exist with a view to defining what bioinformatics and biology will look like in the future.

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Development of the Bibliographic Information Network Prototype for Biology and Life Science (생명과학 문헌정보 네트워크 프로토타입 개발)

  • Ahn, Bu-Young;Song, Chi-Pyoung
    • Journal of Information Management
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    • v.36 no.2
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    • pp.125-151
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    • 2005
  • The eight types of Korean bibliographic information of biology and life science are included in PubMed that serves universal medical bibliographic information. Other domestic bibliographic information are served on its own format at different organizations. To fulfill the CCBB homepage user's request that it is necessary that integration of bibliographic service for quick acquisition of research information, we intends to construct metadata registry and service about bibliographic information of biology and life science. This paper describes the design and implementation of bibliographic information network prototype for biology and life science that can be used to share latest research result, seminar presentation data, research note, and research paper etc as well as to exchange information between researchers through Open Archiving Community.

Guide to Learning Systems Biology for Korean Medicine Researchers (한의학 연구자를 위한 시스템 생물학 학습 가이드)

  • Kim, Chang-Eop
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.30 no.6
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    • pp.412-418
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    • 2016
  • The emergence of systems biology in the 21st century is changing the paradigm of biomedical research. Whereas the reductionist approaches focus on components rather than time or contexts, systems biology focus more on interrelationships, dynamics, and contexts. The key ideas of the systems biology shares much with the philosophy of Korean Medicine(KM) and therefore, the paradigm shift is shedding light on understanding the mechanism of action of KM at system level. In this article, I provide a guide to learning systems biology for KM researchers using online learning resources. Thanks to the recent development of MOOC(massive open online courses) and other online learning platforms, learners can access to plenty of high-quality resources from top-tier universities in the world. I expect this guide help researchers to employ systems biology methods into their KM researches, and will lead to the development of future curricula for training "bi-lingual" experts, KM and computational approaches.