Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.5
2.7
Journals
Applied Sciences
Special Issues
Towards a Systems Biology Approach
share announcement

Towards a Systems Biology Approach

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (28 September 2021) | Viewed by 21266

Special Issue Editors

Dr. Jong Bong Lee

E-Mail Website
Guest Editor
Janssen Research & Development, Spring House, PA, USA
Interests: clinical pharmacology; systems pharmacology; pharmacokinetics; biopharmaceutics; modeling and simulations
Dr. Pavel Gershkovich

E-Mail Website
Guest Editor
School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK
Dr. Tae Hwan Kim

E-Mail
Guest Editor
College of Pharmacy, Daegu Catholic University, D7 408, Hayang-Ro 13-13, Hayang-Eup, Gyeongsan-si, Gyeongbuk 38430, Korea
Interests: pharmacokinetics; pharmacokinetic-pharmacodynamic (PKPD) modeling; physiologically-based pharmacokinetic (PBPK) modeling; quantitative system pharmacology (QSP) modeling; in vivo-in vitro correlation (IVIVC) modeling; drug metabolism/pharmacokinetic screening; pharmaceutical analysis (LC-MS/MS, HPLC)

Special Issue Information

Dear Colleagues,

Advancement in experimental instrumentation and techniques coupled with enhanced computational powers has brought about the evolution of systems biology. This integrates quantifiable data with respective mechanisms to allow the understanding of the broader pathways and systems in the fields of biology, physiology, pharmacology and toxicology. However, it is acknowledged that there still remains much to be revealed in any system and that quantification is not always done for all the observations. Data availability and integrity are vital for the systems biology approach to be successful, and we need to uncover and quantify many more mechanisms and pathways in order to avoid models with excessive uncertainty and unnecessary assumptions.

Therefore, in this Special Issue, we would like to invite manuscripts describing not only successful cases of systems biology approach but also the data that contribute to efforts that enable such an approach. The specific scope of this Special Issue includes but is not limited to:

  • Systems biology approach (encompassing the fields of biology, physiology, pharmacology and toxicology)
  • In vitro, ex vivo and/or in vivo research that contributes to a future systems biology approach
  • Novel experimental approach that uncovers novel data needed for a systems biology approach
  • Novel method for the quantification of observations or improvement in quantitative methods that can be utilized in a systems biology approach
  • Conventional modeling approach including physiology-relevant or physiologically based models that can lead to a systems biology approach
  • Model simulations data based on appropriate assumptions and compelling hypotheses

Dr. Jong Bong Lee
Dr. Pavel Gershkovich
Dr. Tae Hwan Kim
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • systems biology
  • systems pharmacology
  • quantitative sciences
  • modeling and simulations
  • physiologically based model
  • mathematical model

Published Papers (5 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

Jump to: Review

9 pages, 4683 KiB  
Article
Partition Quantitative Assessment (PQA): A Quantitative Methodology to Assess the Embedded Noise in Clustered Omics and Systems Biology Data
by Diego A. Camacho-Hernández, Victor E. Nieto-Caballero, José E. León-Burguete and Julio A. Freyre-González
Appl. Sci. 2021, 11(13), 5999; https://0-doi-org.brum.beds.ac.uk/10.3390/app11135999 - 28 Jun 2021
Viewed by 1630
Abstract
Identifying groups that share common features among datasets through clustering analysis is a typical problem in many fields of science, particularly in post-omics and systems biology research. In respect of this, quantifying how a measure can cluster or organize intrinsic groups is important [...] Read more.
Identifying groups that share common features among datasets through clustering analysis is a typical problem in many fields of science, particularly in post-omics and systems biology research. In respect of this, quantifying how a measure can cluster or organize intrinsic groups is important since currently there is no statistical evaluation of how ordered is, or how much noise is embedded in the resulting clustered vector. Much of the literature focuses on how well the clustering algorithm orders the data, with several measures regarding external and internal statistical validation; but no score has been developed to quantify statistically the noise in an arranged vector posterior to a clustering algorithm, i.e., how much of the clustering is due to randomness. Here, we present a quantitative methodology, based on autocorrelation, in order to assess this problem. Full article
(This article belongs to the Special Issue Towards a Systems Biology Approach)
►▼ Show Figures

Figure 1

17 pages, 3685 KiB  
Article
A Comparative Cross-Platform Meta-Analysis to Identify Potential Biomarker Genes Common to Endometriosis and Recurrent Pregnancy Loss
by Pokhraj Guha, Shubhadeep Roychoudhury, Sobita Singha, Jogen C. Kalita, Adriana Kolesarova, Qazi Mohammad Sajid Jamal, Niraj Kumar Jha, Dhruv Kumar, Janne Ruokolainen and Kavindra Kumar Kesari
Appl. Sci. 2021, 11(8), 3349; https://0-doi-org.brum.beds.ac.uk/10.3390/app11083349 - 08 Apr 2021
Cited by 1 | Viewed by 2751
Abstract
Endometriosis is characterized by unwanted growth of endometrial tissue in different locations of the female reproductive tract. It may lead to recurrent pregnancy loss, which is one of the worst curses for the reproductive age group of human populations around the world. Thus, [...] Read more.
Endometriosis is characterized by unwanted growth of endometrial tissue in different locations of the female reproductive tract. It may lead to recurrent pregnancy loss, which is one of the worst curses for the reproductive age group of human populations around the world. Thus, there is an urgent need for unveiling any common source of origin of both these diseases and connections, if any. Herein, we aimed to identify common potential biomarker genes of these two diseases via in silico approach using meta-analysis of microarray data. Datasets were selected for the study based on certain exclusion criteria. Those datasets were subjected to comparative meta-analyses for the identification of differentially expressed genes (DEGs), that are common to both diagnoses. The DEGs were then subjected to protein-protein networking and subsequent functional enrichment analyses for unveiling their role/function in connecting two diseases. From the analyses, 120 DEGs are reported to be significant out of which four genes have been found to be prominent. These include the CTNNB1, HNRNPAB, SNRPF and TWIST2 genes. The significantly enriched pathways based on the above-mentioned genes are mainly centered on signaling and developmental events. These findings could significantly elucidate the underlying molecular events in endometriosis-based recurrent miscarriages. Full article
(This article belongs to the Special Issue Towards a Systems Biology Approach)
►▼ Show Figures

Figure 1

18 pages, 2376 KiB  
Article
A Serum Metabolomic Signature for the Detection and Grading of Bladder Cancer
by Jacopo Troisi, Angelo Colucci, Pierpaolo Cavallo, Sean Richards, Steven Symes, Annamaria Landolfi, Giovanni Scala, Francesco Maiorino, Alfonso Califano, Marco Fabiano, Gianmarco Silvestre, Federica Mastella, Alessandro Caputo, Antonio D’Antonio and Vincenzo Altieri
Appl. Sci. 2021, 11(6), 2835; https://0-doi-org.brum.beds.ac.uk/10.3390/app11062835 - 22 Mar 2021
Cited by 11 | Viewed by 2909
Abstract
Bladder cancer has a high incidence and is marked by high morbidity and mortality. Early diagnosis is still challenging. The objective of this study was to create a metabolomics-based profile of bladder cancer in order to provide a novel approach for disease screening [...] Read more.
Bladder cancer has a high incidence and is marked by high morbidity and mortality. Early diagnosis is still challenging. The objective of this study was to create a metabolomics-based profile of bladder cancer in order to provide a novel approach for disease screening and stratification. Moreover, the study characterized the metabolic changes associated with the disease. Serum metabolomic profiles were obtained from 149 bladder cancer patients and 81 healthy controls. Different ensemble machine learning models were built in order to: (1) differentiate cancer patients from controls; (2) stratify cancer patients according to grading; (3) stratify patients according to cancer muscle invasiveness. Ensemble machine learning models were able to discriminate well between cancer patients and controls, between high grade (G3) and low grade (G1-2) cancers and between different degrees of muscle invasivity; ensemble model accuracies were ≥80%. Relevant metabolites, selected using the partial least square discriminant analysis (PLS-DA) algorithm, were included in a metabolite-set enrichment analysis, showing perturbations primarily associated with cell glucose metabolism. The metabolomic approach may be useful as a non-invasive screening tool for bladder cancer. Furthermore, metabolic pathway analysis can increase understanding of cancer pathophysiology. Studies conducted on larger cohorts, and including blind trials, are needed to validate results. Full article
(This article belongs to the Special Issue Towards a Systems Biology Approach)
►▼ Show Figures

Figure 1

11 pages, 949 KiB  
Article
Predicting Intestinal and Hepatic First-Pass Metabolism of Orally Administered Testosterone Undecanoate
by Atheer Zgair, Yousaf Dawood, Suhaib M. Ibrahem, Hyun-moon Back, Leonid Kagan, Pavel Gershkovich and Jong Bong Lee
Appl. Sci. 2020, 10(20), 7283; https://0-doi-org.brum.beds.ac.uk/10.3390/app10207283 - 18 Oct 2020
Cited by 4 | Viewed by 4025
Abstract
The bioavailability of orally administered drugs could be impacted by intestinal and hepatic first-pass metabolism. Testosterone undecanoate (TU), an orally administered ester prodrug of testosterone, is significantly subjected to first-pass metabolism. However, the individual contribution of intestinal and hepatic first-pass metabolism is not [...] Read more.
The bioavailability of orally administered drugs could be impacted by intestinal and hepatic first-pass metabolism. Testosterone undecanoate (TU), an orally administered ester prodrug of testosterone, is significantly subjected to first-pass metabolism. However, the individual contribution of intestinal and hepatic first-pass metabolism is not well determined. Therefore, the aim of the current study was to predict the metabolic contribution of each site. The hydrolysis–time profiles of TU incubation in human liver microsomes and Caco-2 cell homogenate were used to predict hepatic and intestinal first-pass metabolism, respectively. The in vitro half-life (t1/2 inv) for the hydrolysis of TU in microsomal mixtures was 28.31 ± 3.51 min. By applying the “well-stirred” model, the fraction of TU that could escape hepatic first-pass metabolism (FH) was predicted as 0.915 ± 0.009. The incubation of TU in Caco-2 cell homogenate yielded t1/2 inv of 109.28 ± 21.42 min, which was applied in a “Q gut” model to estimate the fraction of TU that would escape intestinal first-pass metabolism (FG) as 0.114 ± 0.02. Accordingly, only 11% of the absorbed fraction of TU could escape intestinal metabolism, while 91% can pass through hepatic metabolism. Hence, compared to the liver, the intestinal wall is the main site where TU is significantly metabolised during first-pass effect. Full article
(This article belongs to the Special Issue Towards a Systems Biology Approach)
►▼ Show Figures

Figure 1

Review

Jump to: Research

15 pages, 498 KiB  
Review
Gliclazide: Biopharmaceutics Characteristics to Discuss the Biowaiver of Immediate and Extended Release Tablets
by Bruna de Carvalho Mapa, Lorena Ulhôa Araújo, Neila Márcia Silva-Barcellos, Tamires Guedes Caldeira and Jacqueline Souza
Appl. Sci. 2020, 10(20), 7131; https://0-doi-org.brum.beds.ac.uk/10.3390/app10207131 - 13 Oct 2020
Cited by 9 | Viewed by 9201
Abstract
The lists of essential medicines of the World Health Organization (WHO) and Brazil include gliclazide as an alternative to the oral antidiabetic drug of first choice, metformin, in the treatment of type 2 diabetes mellitus because of its pharmacokinetic profile and few side [...] Read more.
The lists of essential medicines of the World Health Organization (WHO) and Brazil include gliclazide as an alternative to the oral antidiabetic drug of first choice, metformin, in the treatment of type 2 diabetes mellitus because of its pharmacokinetic profile and few side effects. Thus, it is also considered by WHO and the International Pharmaceutical Federation (FIP) as a drug candidate to biowaiver, which is the evaluation of how favorable the biopharmaceutics characteristics are in order to obtain waiver from the relative bioavailability/bioequivalence (RB/BE) studies to register new medicines. This paper presents a review about the solubility, permeability and dissolution of gliclazide. A critical analysis of the information allowed to identify gliclazide as a Biopharmaceutics Classification System (BCS) Class II drug. Therefore, new drugs in immediate release dosage forms will not be eligible for biowaiver. Regarding the extended release dosage forms, besides the limited solubility, no information on the comparative dissolution profile was found, which would be necessary to analyze a possible biowaiver for a smaller dosage. It can be concluded that the registration of new medicines containing gliclazide must undergo RB/BE studies, since there is not enough evidence to recommend the replacement and waiver of such studies for immediate and extended release formulations. Full article
(This article belongs to the Special Issue Towards a Systems Biology Approach)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop