Special Issue "Biotechnology Tools and Genetic Medicine"

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Technologies and Resources for Genetics".

Deadline for manuscript submissions: closed (20 November 2019).

Special Issue Editor

Prof. Juan L. Rodriguez-Flores
Website
Guest Editor
Department of Genetic Medicine, Weill Cornell Medical College, New York, NY 10021, USA
Interests: Development of biotechnology for precision medicine

Special Issue Information

Dear Colleagues,

The contemporary field of biotechnology is defined by software or hardware that innovates either by (1) incorporating concepts, strategies or materials discovered in living organisms into a design, or by (2) applying synthetic concepts, strategies, or materials to the solution of a known problem in a biological discipline. Biotechnology touches a wide range of research and industrial fields, including but not limited to medicine, agriculture, domesticated animal breeding, wildlife conservation, environmental cleanup, and conversion of biomass to energy.

In this Special Issue, we hope to share with the Genes reader community publications that that describe or review innovative concepts, strategies, and materials either (1) discovered in biological systems and applied to solve a problem in medicine, or (2) of synthetic origin but useful for solving a problem in medicine. A relevant example of (1), here referred to as “bio-materials”, is modification of natural systems such as viruses, bacteria, enzymes and antibodies in order to cure human disease. A relevant example of (2), here referred to as “bio-applications”, is application of data science and artificial intelligence techniques to the design of technology for disease screening. The desired impact of the proposed Special Issue is to gather a broad spectrum of experts to formation of a vision of how to use technology to improve human health at both individual and population scales beyond what was previously thought possible.

Prof. Juan L. Rodriguez-Flores
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 papers will be 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. Genes 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 1800 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

  • Biotechnology
  • Biomaterials
  • Genetics
  • Genomics
  • Artificial intelligence
  • Data science
  • Agriculture
  • Animal breeding
  • Wildlife conservation
  • Biofuels
  • Environmental cleanup

Published Papers (2 papers)

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Research

Open AccessArticle
Real-Time Quantitative PCR Analysis of the Expression Pattern of the Hypoglycemic Polypeptide-P Gene in Momordica charantia
Genes 2019, 10(12), 1044; https://doi.org/10.3390/genes10121044 - 16 Dec 2019
Abstract
This study was designed to establish a real-time quantitative polymerase chain reaction (qPCR) method to rapidly and reliably analyze the hypoglycemic polypeptide-P gene expression pattern in Momordica charantia (MC) and to examine its expression changes in different MC accessions, harvesting seasons, and tissue [...] Read more.
This study was designed to establish a real-time quantitative polymerase chain reaction (qPCR) method to rapidly and reliably analyze the hypoglycemic polypeptide-P gene expression pattern in Momordica charantia (MC) and to examine its expression changes in different MC accessions, harvesting seasons, and tissue types. The qPCR results were further verified by using Western blotting (WB). A total of 10 MCs with different accessions were collected and tested in this study. Among the tested accessions, RU5H showed the highest expression level of the polypeptide-P gene. The expression level of the polypeptide-P gene was not only season-related (with the highest in early July) but also tissue-related (with the highest in the seed tissue). In addition, the expression characteristic of the polypeptide-P gene was maturity-related, with the highest expression level in the tender MC. The WB results show that the transcription level of this gene shows an almost similar trend to the corresponding protein expression level. In conclusion, the established qPCR method can rapidly and effectively detect the expression levels of the polypeptide-P gene in MCs with different accessions; furthermore, various factors, including the accessions, harvesting seasons, and tissue types can affect the expression level. Full article
(This article belongs to the Special Issue Biotechnology Tools and Genetic Medicine)
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Open AccessArticle
Identification of Key Genes and Pathways in Pancreatic Cancer Gene Expression Profile by Integrative Analysis
Genes 2019, 10(8), 612; https://doi.org/10.3390/genes10080612 - 13 Aug 2019
Cited by 3
Abstract
Background: Pancreatic cancer is one of the malignant tumors that threaten human health. Methods: The gene expression profiles of GSE15471, GSE19650, GSE32676 and GSE71989 were downloaded from the gene expression omnibus database including pancreatic cancer and normal samples. The differentially expressed genes between [...] Read more.
Background: Pancreatic cancer is one of the malignant tumors that threaten human health. Methods: The gene expression profiles of GSE15471, GSE19650, GSE32676 and GSE71989 were downloaded from the gene expression omnibus database including pancreatic cancer and normal samples. The differentially expressed genes between the two types of samples were identified with the Limma package using R language. The gene ontology functional and pathway enrichment analyses of differentially-expressed genes were performed by the DAVID software followed by the construction of a protein–protein interaction network. Hub gene identification was performed by the plug-in cytoHubba in cytoscape software, and the reliability and survival analysis of hub genes was carried out in The Cancer Genome Atlas gene expression data. Results: The 138 differentially expressed genes were significantly enriched in biological processes including cell migration, cell adhesion and several pathways, mainly associated with extracellular matrix-receptor interaction and focal adhesion pathway in pancreatic cancer. The top hub genes, namely thrombospondin 1, DNA topoisomerase II alpha, syndecan 1, maternal embryonic leucine zipper kinase and proto-oncogene receptor tyrosine kinase Met were identified from the protein–protein interaction network. The expression levels of hub genes were consistent with data obtained in The Cancer Genome Atlas. DNA topoisomerase II alpha, syndecan 1, maternal embryonic leucine zipper kinase and proto-oncogene receptor tyrosine kinase Met were significantly linked with poor survival in pancreatic adenocarcinoma. Conclusions: These hub genes may be used as potential targets for pancreatic cancer diagnosis and treatment. Full article
(This article belongs to the Special Issue Biotechnology Tools and Genetic Medicine)
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