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Biology
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Intelligent Computing in Biology and Medicine II
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Intelligent Computing in Biology and Medicine II

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 5810

Special Issue Editor

Prof. Dr. De-Shuang Huang

E-Mail Website
Guest Editor
Eastern Institute for Advanced Study, Eastern Institute of Technology, Ningbo 315201, China
Interests: bioinformatics; biological image processing; pattern recognition and neural network
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Alongside artificial intelligence (AI) as a hot topic of current research, intelligent computing technology is also a blooming field. Currently, intelligent computing technology is playing an increasingly important role in deriving meaningful and logical conclusions in biology and medicine. Understanding biological and medical data will help in answering important questions of life on earth, finding solutions for global health problems, and even solving problems such as drug design and disease diagnosis. The data generated from biology and medicine possess a variety of unique properties, such as low quality, big dataset size, different complex formats, high dimensionality, many duplications, high noise, etc. All of these properties require a special skill set or unique tools for analysis and interpretation. Thus, research using intelligent computing technology to handle biological and medical data is becoming a very popular topic in the computer science research community.

In this Special Issue focused on Intelligent Computing in Biology and Medicine, we solicit technical papers in the fields of proteomics, molecular recognition, protein folding, bioinformatics, etc., using intelligent computing technology. The aim of this Special Issue is to assemble a collection of manuscripts that showcase the latest research in the field of bioinformatics.

Prof. Dr. De-Shuang Huang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bioinformatics
  • genome
  • protein
  • omics
  • gene expression
  • interaction
  • disease
  • intelligent computing
  • data integration

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Published Papers (2 papers)

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34 pages, 14603 KiB  
Article
Integration of Chemoinformatics and Multi-Omics Analysis Defines ECT2 as a Potential Target for Cancer Drug Therapy
by Mohamed A. Soltan, Muhammad Alaa Eldeen, Bayan H. Sajer, Reda F. A. Abdelhameed, Fawziah A. Al-Salmi, Eman Fayad, Ibrahim Jafri, Hebatallah Emam Mohammed Ahmed, Refaat A. Eid, Hesham M. Hassan, Mubarak Al-Shraim, Amr Negm, Ahmed E. Noreldin and Khaled M. Darwish
Biology 2023, 12(4), 613; https://doi.org/10.3390/biology12040613 - 18 Apr 2023
Cited by 5 | Viewed by 2907
Abstract
Epithelial cell transforming 2 (ECT2) is a potential oncogene and a number of recent studies have correlated it with the progression of several human cancers. Despite this elevated attention for ECT2 in oncology-related reports, there is no collective study to combine and integrate [...] Read more.
Epithelial cell transforming 2 (ECT2) is a potential oncogene and a number of recent studies have correlated it with the progression of several human cancers. Despite this elevated attention for ECT2 in oncology-related reports, there is no collective study to combine and integrate the expression and oncogenic behavior of ECT2 in a panel of human cancers. The current study started with a differential expression analysis of ECT2 in cancerous versus normal tissue. Following that, the study asked for the correlation between ECT2 upregulation and tumor stage, grade, and metastasis, along with its effect on patient survival. Moreover, the methylation and phosphorylation status of ECT2 in tumor versus normal tissue was assessed, in addition to the investigation of the ECT2 effect on the immune cell infiltration in the tumor microenvironment. The current study revealed that ECT2 was upregulated as mRNA and protein levels in a list of human tumors, a feature that allowed for the increased filtration of myeloid-derived suppressor cells (MDSC) and decreased the level of natural killer T (NKT) cells, which ultimately led to a poor prognosis survival. Lastly, we screened for several drugs that could inhibit ECT2 and act as antitumor agents. Collectively, this study nominated ECT2 as a prognostic and immunological biomarker, with reported inhibitors that represent potential antitumor drugs. Full article
(This article belongs to the Special Issue Intelligent Computing in Biology and Medicine II)
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11 pages, 1315 KiB  
Article
In Silico Study of Mangostin Compounds and Its Derivatives as Inhibitors of α-Glucosidase Enzymes for Anti-Diabetic Studies
by Ahmad Fariz Maulana, Sriwidodo Sriwidodo, Yaya Rukayadi and Iman Permana Maksum
Biology 2022, 11(12), 1837; https://doi.org/10.3390/biology11121837 - 16 Dec 2022
Cited by 7 | Viewed by 2316
Abstract
Diabetes is a chronic disease with a high mortality rate worldwide and can cause other diseases such as kidney damage, narrowing of blood vessels, and heart disease. The concomitant use of drugs such as metformin, sulfonylurea, miglitol, and acarbose may cause side effects [...] Read more.
Diabetes is a chronic disease with a high mortality rate worldwide and can cause other diseases such as kidney damage, narrowing of blood vessels, and heart disease. The concomitant use of drugs such as metformin, sulfonylurea, miglitol, and acarbose may cause side effects with long-term administration. Therefore, natural ingredients are the best choice, considering that their long-term side effects are not significant. One of the compounds that can be used as a candidate antidiabetic is mangostin; however, information on the molecular mechanism needs to be further analyzed through molecular docking, simulating molecular dynamics, and testing the in silico antidiabetic potential. This study focused on modeling the protein structure, molecular docking, and molecular dynamics simulations and analyses. This process produces RMSD values, free energies, and intermolecular hydrogen bonding. Based on the analysis results, all molecular dynamics simulations can occur under physiological conditions, and γ-mangostin is the best among the test compounds. Full article
(This article belongs to the Special Issue Intelligent Computing in Biology and Medicine II)
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