Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.1
4.9
Journals
IJMS
Special Issues
Bioinformatics and Systems Biology for Decoding Complex Diseases Molecular Mechanisms
ijms-logo
Submit to IJMS Review for IJMS Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Bioinformatics and Systems Biology for Decoding Complex Diseases Molecular Mechanisms

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 2890

Special Issue Editor

Dr. Iman Tavassoly

E-Mail Website
Guest Editor
Independent Researcher, New York, NY 10029, USA
Interests: systems biology; precision medicine; systems pharmacology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Bioinformatics and Systems Biology are interdisciplinary tools that decode the complexity of diseases across various scales. By integrating big biological data with computational models, these fields provide insights into the complex mechanisms driving diseases, thereby advancing personalized and precision medicine. Investigate complex mechanistic mechanisms by analyzing and interpreting biological information, such as DNA sequences, protein structures, and gene expression, integrating experimental data, computational modeling, and mathematical analysis.

In disease understanding, bioinformatics analyzes vast and complex biological data, including omics data to pinpoint disease-related genes, pathways, and biomarkers. Systems Biology complements this by modeling the interactions within biological systems in time and space, elucidating how biomolecular variations and environmental factors influence disease onset and progression.

Moreover, these methodologies contribute to the development of novel therapeutic and diagnostic approaches by identifying biomarker signatures, facilitating drug discovery, predicting individualized drug responses based on molecular profiles, and optimizing treatment strategies. By unraveling the molecular underpinnings of diseases, bioinformatics and systems biology equip clinicians with invaluable tools for early diagnosis, prognosis, and the tailored development of precision medicine, thereby advancing healthcare towards more effective disease prevention and treatment paradigms.

Dr. Iman Tavassoly
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • complex diseases
  • bioinformatics
  • systems biology

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

28 pages, 4740 KiB  
Article
Elucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates
by Jun Xiao, Yangkun Cao, Xuan Li, Long Xu, Zhihang Wang, Zhenyu Huang, Xuechen Mu, Yinwei Qu and Ying Xu
Int. J. Mol. Sci. 2025, 26(1), 275; https://doi.org/10.3390/ijms26010275 - 31 Dec 2024
Viewed by 815
Abstract
Cancer occurrence rates exhibit diverse age-related patterns, and understanding them may shed new and important light on the drivers of cancer evolution. This study systematically analyzes the age-dependent occurrence rates of 23 carcinoma types, focusing on their age-dependent distribution patterns, the determinants of [...] Read more.
Cancer occurrence rates exhibit diverse age-related patterns, and understanding them may shed new and important light on the drivers of cancer evolution. This study systematically analyzes the age-dependent occurrence rates of 23 carcinoma types, focusing on their age-dependent distribution patterns, the determinants of peak occurrence ages, and the significant difference between the two genders. According to the SEER reports, these cancer types have two types of age-dependent occurrence rate (ADOR) distributions, with most having a unimodal distribution and a few having a bimodal distribution. Our modeling analyses have revealed that (1) the first type can be naturally and simply explained using two age-dependent parameters: the total number of stem cell divisions in an organ from birth to the current age and the availability levels of bloodborne growth factors specifically needed by the cancer (sub)type, and (2) for the second type, the first peak is due to viral infection, while the second peak can be explained as in (1) for each cancer type. Further analyses indicate that (i) the iron level in an organ makes the difference between the male and female cancer occurrence rates, and (ii) the levels of sex hormones are the key determinants in the onset age of multiple cancer types. This analysis deepens our understanding of the dynamics of cancer evolution shared by diverse cancer types and provides new insights that are useful for cancer prevention and therapeutic strategies, thereby addressing critical gaps in the current paradigm of oncological research. Full article
(This article belongs to the Special Issue Bioinformatics and Systems Biology for Decoding Complex Diseases Molecular Mechanisms)
►▼ Show Figures

Figure 1

20 pages, 11510 KiB  
Article
Elucidating the Functional Roles of Long Non-Coding RNAs in Alzheimer’s Disease
by Zhenyu Huang, Qiufen Chen, Xuechen Mu, Zheng An and Ying Xu
Int. J. Mol. Sci. 2024, 25(17), 9211; https://doi.org/10.3390/ijms25179211 - 25 Aug 2024
Cited by 3 | Viewed by 1739
Abstract
Alzheimer’s disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on the elucidation of functional roles played [...] Read more.
Alzheimer’s disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on the elucidation of functional roles played by long non-coding RNAs (lncRNAs) throughout the AD progression. We first assembled our own lncRNA transcripts from the raw RNA-Seq data generated from 527 samples of the dorsolateral prefrontal cortex, resulting in the identification of 31,574 novel lncRNA genes. Based on co-expression analyses between mRNAs and lncRNAs, a co-expression network was constructed. Maximal subnetworks with dense connections were identified as functional clusters. Pathway enrichment analyses were conducted over mRNAs and lncRNAs in each cluster, which served as the basis for the inference of functional roles played by lncRNAs involved in each of the key steps in an AD development model that we have previously built based on transcriptomic data of protein-encoding genes. Detailed information is presented about the functional roles of lncRNAs in activities related to stress response, reprogrammed metabolism, cell polarity, and development. Our analyses also revealed that lncRNAs have the discerning power to distinguish between AD samples of each stage and healthy controls. This study represents the first of its kind. Full article
(This article belongs to the Special Issue Bioinformatics and Systems Biology for Decoding Complex Diseases Molecular Mechanisms)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop