journal: Journal of Integrative Bioinformatics

Impact Factor: 1.5

Open Access Published since January 1, 2017

Journal of Integrative Bioinformatics

ISSN: 1613-4516

Editors-in-Chief: Falk Schreiber, Ralf Hofestädt

Edited by: Jan Baumbach, Ming Chen, Yuriy Orlov, Jens Allmer

Managing Editor: Björn Sommer

Editorial Board: Alejandro Giorgetti, Andrew Harrison, Aleksey Kochetov, Jens Krüger, Qi Ma, Hiroshi Matsuno, Chanchal K. Mitra, Josch K. Pauling, Chris Rawlings, Florentino Fdez-Riverola, Paolo Romano, Richard Röttger, Alban Shoshi, Siomar de Castro Soares, Jan Taubert, Andreas Tauch, Malik Yousef, Stephan Weise, Keywan Hassani-Pak

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About this journal

Objective
Journal of Integrative Bioinformatics (JIB) is an international open access journal publishing original peer-reviewed research articles in all aspects of integrative bioinformatics.

Molecular biology produces huge amounts of data in the post-genomic era. This includes data describing metabolic mechanisms and pathways, structural genomic organization, patterns of regulatory regions; proteomics, transcriptomics, and metabolomics. On the one hand, analysis of this data uses essentially the methods and concepts of computer science; on the other hand, the range of biological tasks solved by researchers determines the range and scope of the data. Currently, there are about 1,000 database systems and various analytical tools available via the Internet which are directed at solving various biological tasks.

The challenge we have is to integrate these list-parts and relationships from genomics and proteomics at novel levels of understanding. Integrative Bioinformatics is a new area of research using the tools of computer science and electronic infrastructure applied to Biotechnology. These tools will also represent the backbone of the concept of a virtual cell.

Topics

Software applications/tools and databases covering the following topics:

Molecular Databases, Information Systems and Data Warehouses
Integration of Data, Methods and Tools
Metabolic and Regulatory Network Modeling and Simulation
Signal Pathways and Cell Control
Network Analysis
Medical Informatics, Biomedicine and Biotechnology
Integrative Approaches for Drug Design
Integrative Data and Text Mining Approaches
Integrative, whole cell and molecular modeling
Visualization and animation

Review papers are also welcome with regard to JIB.tools.

Article formats
Research articles, Review papers, Workshop contributions (if peer-reviewed)

Article processing charges (APCs)
Each unsolicited article, which is accepted for publication in the Journal of Integrative Bioinformatics is subject to an Article Processing Charge of 1,000€.
The Open Access publication of invited articles for Special Issues is sponsored by the editors.

Inquiries concerning APCs should be addressed to the Editorial Office at De Gruyter (see contact details below).

Your Benefits

Dear Authors

We invite your submissions to the Journal of Integrative Bioinformatics (JIB). Please adhere to our instructions for authors and submit your paper online via our submission site at: https://mc.manuscriptcentral.com/dgjib.

Your benefits:

Research using the tools of computer science and electronic infrastructure applied to Biotechnology
High quality single-blind peer-review
International and renowned editorial board
100% Open Access: authors retain the copyright for their work

Follow @JIB_DeGruyter on Twitter!

History

JIB was launched in 2004 as the official Journal of the IMBio association (FG Informationsmanagement in der Biotechnologie of the German Society of Computer Science).

Abstracting and Indexing

Journal of Integrative Bioinformatics is covered by the following services:

Baidu Scholar
Cabells Journalytics
Chronos Hub
CNKI Scholar (China National Knowledge Infrastructure)
CNPIEC - cnpLINKer
DBLP Computer Science Bibliography
Dimensions
DOAJ (Directory of Open Access Journals)
EBSCO (relevant databases)
EBSCO Discovery Service
Engineering Village
GoOA
Google Scholar
Inspec
io-port.net
Japan Science and Technology Agency (JST)
J-Gate
JournalGuide
Medline
MyScienceWork
Naver Academic
Naviga (Softweco)
Primo Central (ExLibris)
Publons
PubMed
PubMed Central
QOAM (Quality Open Access Market)
ReadCube
ScienceON (Korea Institute of Science and Technology Information)
Scilit
SCImago (SJR)
SCOPUS
Semantic Scholar
Sherpa/RoMEO
Summon (ProQuest)
TDNet
Ulrich's Periodicals Directory/ulrichsweb
WanFang Data
Web of Science - Emerging Sources Citation Index
WorldCat (OCLC)
X-MOL
Yewno Discover

Supplementary Materials

Topics

External Links

Volume 21 (2024)

Volume 20 (2023)

Volume 19 (2022)

Volume 18 (2021)

Volume 17 (2020)

Volume 16 (2019)

Volume 15 (2018)

Volume 14 (2017)

Volume 13 (2016)

Volume 12 (2015)

Volume 11 (2014)

Volume 10 (2013)

Volume 9 (2012)

Volume 8 (2011)

Volume 7 (2010)

Volume 6 (2009)

Issue 1

Volume 5 (2008)

Volume 4 (2007)

Volume 3 (2006)

Volume 2 (2005)

Issue 1

Volume 1 (2004)

Issue 1

Journal of Integrative Bioinformatics publishes special and thematic issues focussed on important and emerging topics in the field of study. The journal has established a rigorous process to ensure that any special issue manuscripts follow the same high-quality standards and peer review processes as regular manuscripts. For further information on the journal’s peer review policy please see the "Instructions for Authors".

Recent Special Issues

Journal Impact Factor	1.5	2023, Journal Citation Reports (Clarivate, 2024)
5-year Journal Impact Factor	3.0	2023, Journal Citation Reports (Clarivate, 2024)
Journal Citation Indicator	0.41	2023, Journal Citation Reports (Clarivate, 2024)
CiteScore	3.1	2023, Scopus (Elsevier B.V., 2024)
SCImago Journal Rank	0.388	2023, SJR (Scimago Lab, 2024; Data Source: Scopus)

More information about journal rankings

Submit

Submission
You can easily submit your manuscript online. Simply go to https://mc.manuscriptcentral.com/dgjib and you will be guided through the whole peer-reviewing and publishing process.

Your benefits of publishing with us

High-quality single-blind review process (min. 2 reviewers per manuscript)
Accepted papers will be published online first as DOI-citable, forward-linked articles for quickest possible visibility for the scientific community
Every article easily discoverable because of Search Engine Optimization (SEO) and comprehensive abstracting and indexing services
Secure archiving by De Gruyter and the independent archiving service Portico
Professional sales and marketing activities

Submission process

Submission of your paper via our submission management tool
Peer review process (you will be guided through every step)
Decision on your paper
Online publication

Please note

The journal will only accept papers, which present new tools or new aspects of already JIB published tools. Furthermore, these tools must be available and usable via the internet and free of charge for academician. For accepted review publications you are invited to join JIBtools as an editor for a new topic
In general, the contribution must be clearly structured. This is especially important for long manuscripts. The following arrangement/structure is recommended: Summary, Introduction, Related works, Architecture/Implementation, Application, Discussion, References
It is possible to submit two different types of documents: Microsoft Word or LaTeX, whereas LaTeX is recommended
Before submitting your article please have a look at our Publication Ethics Statement and our Editorial Policy
All authors, agree that the article, if editorially accepted for publication, shall be licensed under the CC BY 4.0 license.
If you have any general questions please visit our FAQ page for authors

We look forward to receiving your manuscript!

Editorial

Editors-in-Chief
Prof. Dr. Ralf Hofestädt, Bielefeld University, Bielefeld, Germany
Prof. Dr. Falk Schreiber, University of Konstanz, Konstanz, Germany

Managing Editor
Dr. Björn Sommer, Royal College of Art, London, UK

Associate Editors
Jens Allmer, Wageningen University & Research, Wageningen, Netherlands
Jan Baumbach, Technical University of Munich, Munich, Germany
Ming Chen, Zhejiang University, Hangzhou, China
Yuriy L. Orlov, Sechnov University - Medical University, Moscow, Russia

Editorial Board
Alejandro Giorgetti, University of Verona, Verona, Italy
Keywan Hassani-Pak, Rothamsted Research, Harpenden, UK
Andrew Harrison, University of Essex, Essex, UK
Aleksey Kochetov, Institute of Cytology and Genetics, Novosibirsk, Russia
Jens Krüger, Tübingen University, Tübingen, Germany
Qi Ma, University of California, San Diego, USA
Hiroshi Matsuno, Yamaguchi University, Yamaguchi, Japan
Chanchal K. Mitra, University of Hyderabad, Hyderabad, India
Josch K. Pauling, Humboldt University, Berlin, Germany
Chris Rawlings, Rothamsted Research, Harpenden, UK
Florentino Fdez-Riverola, University of Vigo, Vigo, Spain
Paolo Romano, IRCCS AOU San Martino IST, Genoa, Italy
Richard Röttger, University of Southern Denmark, Odense, Denmark
Alban Shoshi, Bielefeld University, Bielefeld, Germany
Siomar de Castro Soares, Universidade Federal do Triângulo Mineiro, Uberaba, Brazil
Björn Sommer, University of Konstanz, Konstanz, Germany
Jan Taubert, KWS SAAT AG, Einbeck, Germany
Andreas Tauch, CeBiTec Bielefeld, Bielefeld, Germany
Stephan Weise, IPK Gatersleben, Gatersleben, Germany
Malik Yousef, Zefat Academic College, Zefat, Israel

Scientific contact
JIB Editorial Office
E-Mail: [email protected] or [email protected]

Publisher contact
Torsten Krüger
De Gruyter
Genthiner Straße 13
10785 Berlin
Germany
E-Mail: [email protected]

Volume 21 Issue 4

December 2024

Publicly Available January 6, 2025

Frontmatter

Page range: i-ii

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Computational Integrative Biomedical Approaches to Tackle Human Diseases

Open Access December 11, 2024

TREMSUCS-TCGA – an integrated workflow for the identification of biomarkers for treatment success

Gabor Balogh, Natasha Jorge, Célia Dupain, Maud Kamal, Nicolas Servant, Christophe Le Tourneau, Peter F. Stadler, Stephan H. Bernhart

Article number: 20240031

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Abstract

Many publicly available databases provide disease related data, that makes it possible to link genomic data to medical and meta-data. The cancer genome atlas (TCGA), for example, compiles tens of thousand of datasets covering a wide array of cancer types. Here we introduce an interactive and highly automatized TCGA-based workflow that links and analyses epigenomic and transcriptomic data with treatment and survival data in order to identify possible biomarkers that indicate treatment success. TREMSUCS-TCGA is flexible with respect to type of cancer and treatment and provides standard methods for differential expression analysis or DMR detection. Furthermore, it makes it possible to examine several cancer types together in a pan-cancer type approach. Parallelisation and reproducibility of all steps is ensured with the workflowmanagement system Snakemake. TREMSUCS-TCGA produces a comprehensive single report file which holds all relevant results in descriptive and tabular form that can be explored in an interactive manner. As a showcase application we describe a comprehensive analysis of the available data for the combination of patients with squamous cell carcinomas of head and neck, cervix and lung treated with cisplatin, carboplatin and the combination of carboplatin and paclitaxel. The best ranked biomarker candidates are discussed in the light of the existing literature, indicating plausible causal relationships to the relevant cancer entities.

Open Access December 12, 2024

Exploring the therapeutic potential of Asparagus africanus in polycystic ovarian syndrome: a computational analysis

Sania Riaz, Fatima Haider, Rizwan- ur-Rehman, Aqsa Zafar

Article number: 20240019

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Abstract

PCOS is a multifaceted condition characterized by ovarian abnormalities, metabolic disorders, anovulation, and hormonal imbalances. In response to the growing demand for treatments with fewer side effects, the exploration of herbal-origin drugs has gained prominence. Asparagus africanus , a traditional medicinal plant that exhibits anti-inflammatory, antioxidant, and anti-androgenic properties may have a cure for PCOS. The plant has rich biochemical profile prompted its exploration as a potential source for drug development. The aim of this study is to investigate the potential therapeutic efficacy of A. africanus in the management of PCOS through molecular docking studies with Luteinizing Hormone Receptor and Follicle-Stimulating Hormone Receptor proteins. The identified compounds underwent molecular docking against key proteins associated with PCOS, namely Luteinizing Hormone Receptor and Follicle-Stimulating Hormone Receptor. The results underscored the lead compound’s superiority, demonstrating favorable pharmacokinetics, ADME characteristics, and strong molecular binding without any observed toxicity in comparison to standard drug. This study, by leveraging natural compounds sourced from A. africanus , provides valuable insights and advances towards developing more effective and safer treatments for PCOS. The findings contribute to the evolving landscape of PCOS therapeutics, emphasizing the potential of herbal-origin drugs in mitigating the complexities of this syndrome.

Open Access December 25, 2024

MiRNA target enrichment analysis of co-expression network modules reveals important miRNAs and their roles in breast cancer progression

Mohammad Javad Bazyari, Seyed Hamid Aghaee-Bakhtiari

Article number: 20220036

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Abstract

Breast cancer has the highest incidence and is the fifth cause of death in cancers. Progression is one of the important features of breast cancer which makes it a life-threatening cancer. MicroRNAs are small RNA molecules that have pivotal roles in the regulation of gene expression and they control different properties in breast cancer such as progression. Recently, systems biology offers novel approaches to study complicated biological systems like miRNAs to find their regulatory roles. One of these approaches is analysis of weighted co-expression network in which genes with similar expression patterns are considered as a single module. Because the genes in one module have similar expression, it is rational to think the same regulatory elements such as miRNAs control their expression. Herein, we use WGCNA to find important modules related to breast cancer progression and use hypergeometric test to perform miRNA target enrichment analysis and find important miRNAs. Also, we use negative correlation between miRNA expression and modules as the second filter to ensure choosing the right candidate miRNAs regarding to important modules. We found hsa-mir-23b, hsa-let-7b and hsa-mir-30a are important miRNAs in breast cancer and also investigated their roles in breast cancer progression.

Open Access September 17, 2024

The potential of Mitragyna speciosa leaves as a natural source of antioxidants for disease prevention

Ihsanul Arief, Gagus Ketut Sunnardianto, Syahrul Khairi, Wahyu Dita Saputri

Article number: 20230030

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Abstract

Mitragyna speciosa is famous for its addictive effect. On the other hand, this plant has good potential as an antioxidant agent, and so far, it was not explicitly explained what the most contributing compound in the leaves to that activity is. This study has been conducted using several computational methods to determine which compounds are the most active in interacting with cytochrome P450, myeloperoxidase, and NADPH oxidase proteins. First, virtual screening was carried out based on molecular docking, followed by profiling the properties of adsorption, distribution, metabolism, excretion, and toxicity (ADMET); the second one is the molecular dynamics (MD) simulations for 100 ns. The virtual screening results showed that three compounds acted as inhibitors for each protein: (-)-epicatechin, sitogluside, and corynoxeine. The ADMET profiles of the three compounds exhibit good drug ability and toxicity. The trajectories study from MD simulations predicts that the complexes of these three compounds with their respective target proteins are stable. Furthermore, these compounds identified in this computational study can be a potential guide for future experiments aimed at assessing the antioxidant properties through in vitro testing.

Regular Contribution

Open Access November 25, 2024

Ion channel classification through machine learning and protein language model embeddings

Hamed Ghazikhani, Gregory Butler

Article number: 20230047

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Abstract

Ion channels are critical membrane proteins that regulate ion flux across cellular membranes, influencing numerous biological functions. The resource-intensive nature of traditional wet lab experiments for ion channel identification has led to an increasing emphasis on computational techniques. This study extends our previous work on protein language models for ion channel prediction, significantly advancing the methodology and performance. We employ a comprehensive array of machine learning algorithms, including k-Nearest Neighbors, Random Forest, Support Vector Machines, and Feed-Forward Neural Networks, alongside a novel Convolutional Neural Network (CNN) approach. These methods leverage fine-tuned embeddings from ProtBERT, ProtBERT-BFD, and MembraneBERT to differentiate ion channels from non-ion channels. Our empirical findings demonstrate that TooT-BERT-CNN-C, which combines features from ProtBERT-BFD and a CNN, substantially surpasses existing benchmarks. On our original dataset, it achieves a Matthews Correlation Coefficient (MCC) of 0.8584 and an accuracy of 98.35 %. More impressively, on a newly curated, larger dataset (DS-Cv2), it attains an MCC of 0.9492 and an ROC AUC of 0.9968 on the independent test set. These results not only highlight the power of integrating protein language models with deep learning for ion channel classification but also underscore the importance of using up-to-date, comprehensive datasets in bioinformatics tasks. Our approach represents a significant advancement in computational methods for ion channel identification, with potential implications for accelerating research in ion channel biology and aiding drug discovery efforts.

(Deutsch)

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Type: Journal
Language: English
Publisher: De Gruyter
First published: January 1, 2017
Publication Frequency: 4 Issues per Year