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Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10

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A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 27680

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Special Issue Editors

Dr. Javier De Las Rivas

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Guest Editor

Bioinformatics and Functional Genomics Group, Cancer Research Center (CiC-IBMCC, CSIC/USAL), Consejo Superior de Investigaciones Científicas (CSIC) University of Salamanca (USAL), and Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
Interests: bioinformatics; computational biology; functional genomics; cancer; human gene; cancer gene; genomic medicine; transcriptomics; proteomics; protein interactions; interactome; network biology; data science; artificial intelligence
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Dr. Elizabeth Tapia

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Guest Editor

BioAgroInformatics Group, CIFASIS-CONICET-UNR Institute, Faculty of Electrical Engineering, National University of Rosario, Rosario, Argentina
Interests: Dr. Elizabeth Tapia is full time professor at the Faculty of Electrical Engineering, National University of Rosario, and head of the BioAgroInformatics group of CIFASIS, Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas, a research institute of the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) of the National Council for Science and Technology of Argentina. Over the last years, the research of her group has been focused on the development of bioinformatics solutions based on the combination of machine learning and information theory methods. She currently works in the design of computational methods for the automated annotation of genes in non-model organisms and in the design of robust tags for full-length third-generation sequencing technologies.

Special Issue Information

Dear Colleagues,

ALL registered participants in the #SoIBio+10 Conference (28–30 October 2019, Montevideo, UR) can propose publishing a full research PAPER to a Special Issue of Biomolecules.

A selection of about 12 full articles will be done to be published in the journal Biomolecules (https://www.mdpi.com/journal/biomolecules), in the Special Issue called "Bioinformatics for Precision Biomolecular Data Mining: Progress in Latin America - Selected Papers from the X International Conference on Bioinformatics #SoIBio+10". This special issue will be included in the section of this Journal: "Bioinformatics and Systems Biology".

PLEASE, SUBMIT your PAPER according to the following conditions and dates:

Up to 30 November 2019. FULL PAPER SUBMISSION in the website of the Journal — Submission of the FULL PAPER following the regular format asked by Biomolecules (see Instructions for Authors - Submission Guidelines)
From 1 to 24 December 2019. PEER REVIEW — Time for review of each submitted article by at least 2 independent reviewers. The reviewers will be contacted by the Editorial Office keeping in copy to the Special Editors. At the end of this process, the Editorial Office and the Editors will indicate to the authors which are the final ACCEPTED ARTICLES. (Written reviews and answers will be needed along all this process).
From 25 December 2019 to 15 January 2020. SUBMISSION FOR PUBLICATION — Submission of the final article, revised and corrected. The manuscripts should be prepared for publication following Biomolecules Special Issue Submission Guidelines. Once received by the journal, the editorial office from Biomolecules will get the final edition and publication on-line as soon as it is finalized. AT THIS POINT, the authors of each article (or their institutions) should pay to Biomolecules the "Article-Processing Charges" (APC) that will be: 960 CHF (corresponding to about 970 USD) This price represents a 20% reduction on the normal price of an article in Biomolecules. Biomolecules MDPI editorial office will provide a formal INVOICE to the authors of each accepted article.

All communication about proposals and articles should be made to this mail:

The EDITORS of this Biomolecules Special Issue will be:
- Professor Dr. Javier De Las Rivas (jrivas@usal.es) (University of Salamanca/CSIC, Spain)
- Professor Dra. Elizabeth Tapia (tapia@cifasis-conicet.gov.ar) (University of Rosario/CONICET, Argentina)

BIOMOLECULES (ISSN 2218-273X; CODEN: BIOMHC) is a peer-reviewed Open Access journal on biogenic substances (including but not limiting to proteins, nucleic acids, polysaccharides, membranes, lipids, metabolites, etc) published monthly online by MDPI. The Journal has an Impact Factor: 4.694 (2018), and a Ranking 33/407 (Q1) in 'Biochemistry' and 44/375 (Q1) in 'Molecular Biology'. SEE: https://www.mdpi.com/journal/biomolecules

Dr. Javier De Las Rivas
Dr. Elizabeth Tapia
Guest Editors

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. Biomolecules 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.

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Published Papers (6 papers)

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Research

19 pages, 1621 KiB

Open AccessArticle

Exomes of Ductal Luminal Breast Cancer Patients from Southwest Colombia: Gene Mutational Profile and Related Expression Alterations

by Carolina Cortes-Urrea, Fernando Bueno-Gutiérrez, Melissa Solarte, Miguel Guevara-Burbano, Fabian Tobar-Tosse, Patricia E. Vélez-Varela, Juan Carlos Bonilla, Guillermo Barreto, Jaime Velasco-Medina, Pedro A. Moreno and Javier De Las Rivas

Biomolecules 2020, 10(5), 698; https://doi.org/10.3390/biom10050698 - 30 Apr 2020

Cited by 6 | Viewed by 4908

Abstract

Cancer is one of the leading causes of mortality worldwide. Breast cancer is the most frequent cancer in women, and in recent years it has become a serious public health problem in Colombia. The development of large-scale omic techniques allows simultaneous analysis of all active genes in tumor cells versus normal cells, providing new ways to discover the drivers of malignant transformations. Whole exome sequencing (WES) was obtained to provide a deep view of the mutational genomic profile in a set of cancer samples from Southwest Colombian women. WES was performed on 52 tumor samples from patients diagnosed with invasive breast cancer, which in most cases (33/52) were ductal luminal breast carcinomas (IDC-LM-BRCA). Global variant call was calculated, and six different algorithms were applied to filter out false positives and identify pathogenic variants. To compare and expand the somatic tumor variants found in the Colombian cohort, exome mutations and genome-wide expression alterations were detected in a larger set of tumor samples of the same breast cancer subtype from TCGA (that included DNA-seq and RNA-seq data). Genes with significant changes in both the mutational and expression profiles were identified, providing a set of genes and mutations associated with the etiology of ductal luminal breast cancer. This set included 19 single mutations identified as tumor driver mutations in 17 genes. Some of the genes (ATM, ERBB3, ESR1, TP53) are well-known cancer genes, while others (CBLB, PRPF8) presented driver mutations that had not been reported before. In the case of the CBLB gene, several mutations were identified in TCGA IDC-LM-BRCA samples associated with overexpression of this gene and repression of tumor suppressive activity of TGF-β pathway. Full article

(This article belongs to the Special Issue Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10)

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16 pages, 3666 KiB

Open AccessArticle

Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations

by Monica M. Arroyo, Alberto Berral-González, Santiago Bueno-Fortes, Diego Alonso-López and Javier De Las Rivas

Biomolecules 2020, 10(5), 667; https://doi.org/10.3390/biom10050667 - 25 Apr 2020

Cited by 13 | Viewed by 4966

Abstract

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs. Full article

(This article belongs to the Special Issue Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10)

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15 pages, 7956 KiB

Open AccessArticle

Calculation of the Geometries and Infrared Spectra of the Stacked Cofactor Flavin Adenine Dinucleotide (FAD) as the Prerequisite for Studies of Light-Triggered Proton and Electron Transfer

by Martina Kieninger, Oscar N. Ventura and Tilman Kottke

Biomolecules 2020, 10(4), 573; https://doi.org/10.3390/biom10040573 - 9 Apr 2020

Cited by 3 | Viewed by 3812

Abstract

Flavin cofactors, like flavin adenine dinucleotide (FAD), are important electron shuttles in living systems. They catalyze a wide range of one- or two-electron redox reactions. Experimental investigations include UV-vis as well as infrared spectroscopy. FAD in aqueous solution exhibits a significantly shorter excited state lifetime than its analog, the flavin mononucleotide. This finding is explained by the presence of a “stacked” FAD conformation, in which isoalloxazine and adenine moieties form a π-complex. Stacking of the isoalloxazine and adenine rings should have an influence on the frequency of the vibrational modes. Density functional theory (DFT) studies of the closed form of FAD in microsolvation (explicit water) were used to reproduce the experimental infrared spectra, substantiating the prevalence of the stacked geometry of FAD in aqueous surroundings. It could be shown that the existence of the closed structure in FAD can be narrowed down to the presence of only a single water molecule between the third hydroxyl group (of the ribityl chain) and the N7 in the adenine ring of FAD. Full article

(This article belongs to the Special Issue Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10)

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17 pages, 8981 KiB

Open AccessArticle

Deciphering Master Gene Regulators and Associated Networks of Human Mesenchymal Stromal Cells

by Elena Sánchez-Luis, Andrea Joaquín-García, Francisco J. Campos-Laborie, Fermín Sánchez-Guijo and Javier De las Rivas

Biomolecules 2020, 10(4), 557; https://doi.org/10.3390/biom10040557 - 5 Apr 2020

Cited by 8 | Viewed by 5301

Abstract

Mesenchymal Stromal Cells (MSC) are multipotent cells characterized by self-renewal, multilineage differentiation, and immunomodulatory properties. To obtain a gene regulatory profile of human MSCs, we generated a compendium of more than two hundred cell samples with genome-wide expression data, including a homogeneous set of 93 samples of five related primary cell types: bone marrow mesenchymal stem cells (BM-MSC), hematopoietic stem cells (HSC), lymphocytes (LYM), fibroblasts (FIB), and osteoblasts (OSTB). All these samples were integrated to generate a regulatory gene network using the algorithm ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks; based on mutual information), that finds regulons (groups of target genes regulated by transcription factors) and regulators (i.e., transcription factors, TFs). Furtherly, the algorithm VIPER (Algorithm for Virtual Inference of Protein-activity by Enriched Regulon analysis) was used to inference protein activity and to identify the most significant TF regulators, which control the expression profile of the studied cells. Applying these algorithms, a footprint of candidate master regulators of BM-MSCs was defined, including the genes EPAS1, NFE2L1, SNAI2, STAB2, TEAD1, and TULP3, that presented consistent upregulation and hypomethylation in BM-MSCs. These TFs regulate the activation of the genes in the bone marrow MSC lineage and are involved in development, morphogenesis, cell differentiation, regulation of cell adhesion, and cell structure. Full article

(This article belongs to the Special Issue Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10)

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14 pages, 1121 KiB

Open AccessArticle

Consistency of the Tools That Predict the Impact of Single Nucleotide Variants (SNVs) on Gene Functionality: The BRCA1 Gene

by Javier Murillo, Flavio Spetale, Serge Guillaume, Pilar Bulacio, Ignacio Garcia Labari, Olivier Cailloux, Sebastien Destercke and Elizabeth Tapia

Biomolecules 2020, 10(3), 475; https://doi.org/10.3390/biom10030475 - 20 Mar 2020

Viewed by 2884

Abstract

Single nucleotide variants (SNVs) occurring in a protein coding gene may disrupt its function in multiple ways. Predicting this disruption has been recognized as an important problem in bioinformatics research. Many tools, hereafter p-tools, have been designed to perform these predictions and many of them are now of common use in scientific research, even in clinical applications. This highlights the importance of understanding the semantics of their outputs. To shed light on this issue, two questions are formulated, (i) do p-tools provide similar predictions? (inner consistency), and (ii) are these predictions consistent with the literature? (outer consistency). To answer these, six p-tools are evaluated with exhaustive SNV datasets from the BRCA1 gene. Two indices, called

K_{a l l}

and

K_{s t r o n g}

, are proposed to quantify the inner consistency of pairs of p-tools while the outer consistency is quantified by standard information retrieval metrics. While the inner consistency analysis reveals that most of the p-tools are not consistent with each other, the outer consistency analysis reveals they are characterized by a low prediction performance. Although this result highlights the need of improving the prediction performance of individual p-tools, the inner consistency results pave the way to the systematic design of truly diverse ensembles of p-tools that can overcome the limitations of individual members. Full article

(This article belongs to the Special Issue Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10)

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21 pages, 1960 KiB

Open AccessArticle

The Ovarian Transcriptome of Reproductively Aged Multiparous Mice: Candidate Genes for Ovarian Cancer Protection

by Ulises Urzúa, Carlos Chacón, Maximiliano Norambuena, Luis Lizama, Sebastián Sarmiento, Esther Asaki, John I Powell and Sandra Ampuero

Biomolecules 2020, 10(1), 113; https://doi.org/10.3390/biom10010113 - 9 Jan 2020

Cited by 6 | Viewed by 4764

Abstract

In middle-aged women, the decline of ovarian follicle reserve below a critical threshold marks menopause, leading to hormonal, inflammatory, and metabolic changes linked to disease. The highest incidence and mortality of sporadic ovarian cancer (OC) occur at post-menopause, while OC risk is reduced by full-term pregnancies during former fertile life. Herein, we investigate how parity history modulates the ovarian transcriptome related to such declining follicle pool and systemic inflammation in reproductively-aged mice. Female C57BL/6 mice were housed under multiparous and virgin (nulliparous) breeding regimens from adulthood until estropause. The ovaries were then subjected to follicle count and transcriptional profiling, while a cytokine panel was determined in the sera. As expected, the follicle number was markedly decreased just by aging. Importantly, a significantly higher count of primordial and total follicles was observed in aged multiparous relative to aged virgin ovaries. Consistently, among the 65 genes of higher expression in aged multiparous ovaries, 27 showed a follicle count-like pattern, 21 had traceable evidence of roles in follicular/oocyte homeostasis, and 7 were transforming-growth factor beta (TGF-β)/bone morphogenetic protein (BMP) superfamily members. The remaining genes were enriched in cell chemotaxis and innate-immunity, and resembled the profiles of circulating CXCL1, CXCL2, CXCL5, CSF3, and CCL3, chemokines detected at higher levels in aged multiparous mice. We conclude that multiparity during reproductive life promotes the retention of follicle remnants while improving local (ovarian) and systemic immune-innate surveillance in aged female mice. These findings could underlie the mechanisms by which pregnancy promotes the long-term reduced OC risk observed at post-menopause. Full article

(This article belongs to the Special Issue Bioinformatics and Precision Computational Biology: Selected Papers from the X International Conference on Bioinformatics #SoIBio+10)

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