ijms-logo

Journal Browser

Journal Browser

Computational Medicine and Bioinformatics Research

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 (15 November 2023) | Viewed by 7222

Special Issue Editor

Special Issue Information

Dear Colleagues, 

The Special Issue is dedicated to different topics in computational medicine and bioinformatics, which require the use of mathematical or statistical models:

  • Modeling of the epidemic spread;
  • Modeling of the contagion mechanisms;
  • Modeling of molecular steps explaining viral virulence and mutability;
  • Biostatistics and infectious diseases;
  • Modeling of the mechanisms of obesity;
  • Modeling of the mechanisms of innate immunity and adaptive immunity;
  • Bioinformatics and evolution of ribosomal translation mechanisms;
  • Bioinformatics and evolution of transcription mechanisms.

Prof. Dr. Jacques Demongeot
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.

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Other

15 pages, 1668 KiB  
Article
Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients
by Isabel Fernández-Pérez, Joan Jiménez-Balado, Uxue Lazcano, Eva Giralt-Steinhauer, Lucía Rey Álvarez, Elisa Cuadrado-Godia, Ana Rodríguez-Campello, Adrià Macias-Gómez, Antoni Suárez-Pérez, Anna Revert-Barberá, Isabel Estragués-Gázquez, Carolina Soriano-Tarraga, Jaume Roquer, Angel Ois and Jordi Jiménez-Conde
Int. J. Mol. Sci. 2023, 24(3), 2759; https://doi.org/10.3390/ijms24032759 - 1 Feb 2023
Cited by 1 | Viewed by 2592
Abstract
Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk [...] Read more.
Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum’s epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (R2 0.358 and 0.378, respectively). In conclusion, our results support the influence of these factors on Age-A; although, they were not enough to explain most of its variability. Full article
(This article belongs to the Special Issue Computational Medicine and Bioinformatics Research)
Show Figures

Figure 1

15 pages, 1069 KiB  
Article
Variant-Specific Analysis Reveals a Novel Long-Range RNA-RNA Interaction in SARS-CoV-2 Orf1a
by Matthew Dukeshire, David Schaeper, Pravina Venkatesan and Amirhossein Manzourolajdad
Int. J. Mol. Sci. 2022, 23(19), 11050; https://doi.org/10.3390/ijms231911050 - 21 Sep 2022
Cited by 2 | Viewed by 1672
Abstract
Since the start of the COVID-19 pandemic, understanding the pathology of the SARS-CoV-2 RNA virus and its life cycle has been the priority of many researchers. Currently, new variants of the virus have emerged with various levels of pathogenicity and abundance within the [...] Read more.
Since the start of the COVID-19 pandemic, understanding the pathology of the SARS-CoV-2 RNA virus and its life cycle has been the priority of many researchers. Currently, new variants of the virus have emerged with various levels of pathogenicity and abundance within the human-host population. Although much of viral pathogenicity is attributed to the viral Spike protein’s binding affinity to human lung cells’ ACE2 receptor, comprehensive knowledge on the distinctive features of viral variants that might affect their life cycle and pathogenicity is yet to be attained. Recent in vivo studies into the RNA structure of the SARS-CoV-2 genome have revealed certain long-range RNA-RNA interactions. Using in silico predictions and a large population of SARS-CoV-2 sequences, we observed variant-specific evolutionary changes for certain long-range RRIs. We also found statistical evidence for the existence of one of the thermodynamic-based RRI predictions, namely Comp1, in the Beta variant sequences. A similar test that disregarded sequence variant information did not, however, lead to significant results. When performing population-based analyses, aggregate tests may fail to identify novel interactions due to variant-specific changes. Variant-specific analyses can result in de novo RRI identification. Full article
(This article belongs to the Special Issue Computational Medicine and Bioinformatics Research)
Show Figures

Figure 1

Other

Jump to: Research

9 pages, 1579 KiB  
Hypothesis
Primitive Oligomeric RNAs at the Origins of Life on Earth
by Jacques Demongeot and Michel Thellier
Int. J. Mol. Sci. 2023, 24(3), 2274; https://doi.org/10.3390/ijms24032274 - 23 Jan 2023
Cited by 3 | Viewed by 1721
Abstract
There are several theories on the origin of life, which differ by choosing the preponderant factor of emergence: main function (autocatalysis versus replication), initial location (black smokers versus ponds) or first molecule (RNA versus DNA). Among the two last ones, the first assumes [...] Read more.
There are several theories on the origin of life, which differ by choosing the preponderant factor of emergence: main function (autocatalysis versus replication), initial location (black smokers versus ponds) or first molecule (RNA versus DNA). Among the two last ones, the first assumes that an RNA world involving a collaboration of small RNAs with amino-acids pre-existed and the second that DNA–enzyme–lipid complexes existed first. The debate between these classic theories is not closed and the arguments for one or the other of these theories have recently fueled a debate in which the two have a high degree of likelihood. It therefore seems interesting to propose a third intermediate way, based on the existence of an RNA that may have existed before the latter stages postulated by these theories, and therefore may be the missing link towards a common origin of them. To search for a possible ancestral structure, we propose as candidate a small RNA existing in ring or hairpin form in the early stages of life, which could have acted as a “proto-ribosome” by favoring the synthesis of the first peptides. Remnants of this putative candidate RNA exist in molecules nowadays involved in the ribosomal factory, the concentrations of these relics depending on the seniority of these molecules within the translation process. Full article
(This article belongs to the Special Issue Computational Medicine and Bioinformatics Research)
Show Figures

Figure 1

Back to TopTop