Bioinformatics and Its Application in Biomedicine 2.0

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 2494

Special Issue Editor


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Guest Editor
1. Department of Medicine I, Institute of Cancer Research and Comprehensive Cancer Center, Medical University Vienna, Vienna, Austria
2. ScienceConsult - DI Thomas Mohr KG, Enzianweg 10a, 2353 Guntramsdorf, Austria
Interests: bioinformatics; systems biology; cancer; biomarker identification; network analysis; omics analysis; in-vitro test development; data integration
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Special Issue Information

Dear Colleagues,

Bioinformatics has become an indispensable tool in molecular biology. Analytic tools provided by bioinformaticians have allowed unprecedented insights into many aspects of medicine. For example, the generation and analysis of omics data in the context of biologic functions and pathways has permitted revolutionary advancements in terms of disease classification and the identification of therapeutic targets and biomarkers.

This Special Issue aims at describing state-of-the-art methods in bioinformatics and their application in biomedicine. The main topics covered will be:

  • The analysis of genomics, transcriptomics, proteomics and metabolomics data;
  • The determination of the biologic contexts of omics data;
  • The integration of omics data;
  • The analysis of gene-gene interaction networks;
  • In silico dissection;
  • The determination of biomarkers using network-based methods and AI;
  • What are the current trends in bioinformatics?

The focus will be on papers linking bioinformatics and the wet lab; therefore, they should ideally include confirmatory experiments. However, papers will be considered case by case based on overall merit.

Dr. Thomas Mohr
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. Biomedicines 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 2600 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

  • genomics
  • transcriptomics
  • proteomics
  • metabolomics
  • biologic context of omics data
  • integration of omics techniques
  • co-expression network analysis
  • gene-gene interaction networks
  • artificial intelligence in molecular biology

Published Papers (1 paper)

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Research

13 pages, 2381 KiB  
Article
Evaluation and Comparison of Multi-Omics Data Integration Methods for Subtyping of Cutaneous Melanoma
by Adriana Amaro, Max Pfeffer, Ulrich Pfeffer and Francesco Reggiani
Biomedicines 2022, 10(12), 3240; https://doi.org/10.3390/biomedicines10123240 - 13 Dec 2022
Cited by 3 | Viewed by 2006
Abstract
There is a growing number of multi-domain genomic datasets for human tumors. Multi-domain data are usually interpreted after separately analyzing single-domain data and integrating the results post hoc. Data fusion techniques allow for the real integration of multi-domain data to ideally improve the [...] Read more.
There is a growing number of multi-domain genomic datasets for human tumors. Multi-domain data are usually interpreted after separately analyzing single-domain data and integrating the results post hoc. Data fusion techniques allow for the real integration of multi-domain data to ideally improve the tumor classification results for the prognosis and prediction of response to therapy. We have previously described the joint singular value decomposition (jSVD) technique as a means of data fusion. Here, we report on the development of these methods in open source code based on R and Python and on the application of these data fusion methods. The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) dataset was used as a benchmark to evaluate the potential of the data fusion approaches to improve molecular classification of cancers in a clinically relevant manner. Our data show that the data fusion approach does not generate classification results superior to those obtained using single-domain data. Data from different domains are not entirely independent from each other, and molecular classes are characterized by features that penetrate different domains. Data fusion techniques might be better suited for response prediction, where they could contribute to the identification of predictive features in a domain-independent manner to be used as biomarkers. Full article
(This article belongs to the Special Issue Bioinformatics and Its Application in Biomedicine 2.0)
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