International Journal of Computational Biology and Drug Design
- Editor in Chief
- Dr. Zhongming Zhao
- ISSN online
- ISSN print
- 6 issues per year
- CiteScore 0.6 (2021)
IJCBDD, an International Society of Intelligent Biological Medicine official journal, bridges the gap between two very important, complementary disciplines, computational biology and drug design. Through advances in high-throughput genome sequencing and digital imaging technologies, biocomputing, drug design and medical research have unfolded new, predictive sciences such as genomics, proteomics, lipidomics, metabolomics, cytomics and pharmaconomics. These promote new computational, statistical and biomedical approaches to drug design/development, besides unleashing the potential of significantly more accurate, effective personalised diagnosis, therapeutics and patient care.
Topics covered include
- Big data analysis and tools for biological and medical data
- Drug screening, drug discovery, drug design and re-purposing
- Biomolecular dynamics, biomolecular/phylogenetic databases
- Cellular signalling/communications, cell engineering, molecular/cellular systems
- Computational epigenetics and functional genomics
- Computational approaches in virus omics and drug targets
- Machine learning, deep learning, data mining and knowledge discovery
- Metabolomics, microbiomes and lipidomics
- Modelling, simulation and optimisation of biological systems
- Non-coding RNAs and regulation
- Medical informatics and translational informatics
- Cohort discovery, EHR-based phenotyping, predictive modelling
- Proteomics, structural biology, molecular simulation and evolution
- Single cell sequencing methods and analysis
- Software, tools, databases and web servers for computational biology
The objectives of IJCBDD are to promote dialogue among researchers from multiple disciplines and the advancement of innovative biotechnology, biological, medical and pharmaceutical sciences. The journal also seeks to establish an effective communication channel between government agencies and academic and research institutions.
The audience of IJCBDD consists of scientists, researchers, medical and pharmaceutical practitioners, academics, graduate students, professionals and engineers working and interested in learning about new trends in computational biology and drug design.
IJCBDD publishes original papers, application papers, review papers, technical reports, case studies, conference reports, management reports, book reviews, notes, commentaries, and news. Special Issues devoted to important research topics and major international conferences in the fields will occasionally be published
IJCBDD is indexed in:
- Scopus (Elsevier)
- Academic OneFile (Gale)
- BIOSIS (Clarivate Analytics)
- Chemical Abstracts (CAS)
- cnpLINKer (CNPIEC)
- DBLP Computer Science Bibliography
- Embase (Elsevier)
- Expanded Academic ASAP (Gale)
- Google Scholar
- Info Trac (Gale)
- ProQuest Advanced Technologies Database with Aerospace
IJCBDD is listed in:More journal lists/directories...
Editor in Chief
- Zhao, Zhongming, University of Texas Health Science Center at Houston, USA
- Xia, Junfeng, Anhui University, China
- Chang, Jeffrey T., University of Texas Health Science Center at Houston, USA
- Altman, Russ B., Stanford University, USA
- Athey, Brian D., University of Michigan Medical School, USA
- Bajcsy, Ruzena, University of Pennsylvania, USA
- Dunker, A. Keith, Indiana University-Purdue University Indianapolis, USA
- Li, Lang, The Ohio State University, USA
- Niemierko, Andrzej, Harvard Medical School and Massachusetts General Hospital, USA
- Xu, Dong, University of Missouri, USA
Editorial Board Members
- Ancukiewicz, Marek, Harvard Medical School and Massachusetts General Hospital, USA
- Bai, Yongsheng, Indiana State University, USA
- Chen, Yu Zong, National University of Singapore, Singapore
- Ewing, Rob M., Case Western Reserve University, USA
- Feng, Hao (Harry), Case Western Reserve University, USA
- Gaur, Loveleen, Amity University, India
- Ghosh, Joydeep, University of Texas Austin, USA
- Guo, Yan, University of New Mexico, USA
- Honavar, Vasant, Iowa State University, USA
- Jain, Vishal, Bharati Vidyapeeth's Institute of Computer Applications and Management (BVICAM), India
- Jia, Peilin, University of Texas Health Science Center at Houston, USA
- Korkin, Dmitry, University of Missouri, USA
- Li, Aimin, Xi’an University of Technology, China
- Liu, Zhandong, Baylor College of Medicine, USA
- Pan, Yi, Georgia State University, USA
- Qian, Jiang, Johns Hopkins University, USA
- Ramanathan, K., Vellore Institute of Technology, India
- Shang, Xuequn, Northwestern Polytechnical University, China
- Wan, Jun, Indiana University, USA
- Wei, Lei, Roswell Park Cancer Center, USA
- Xie, Lei, City University of New York, USA
- Zhang, Chi, Indiana University, USA
- Zhang, Yongqing, Chengdu University of Information Technology, China
- Zhao, Qi, Liaoning University, China
- Zhao, Yichuan, Georgia State University, USA
- Zheng, Huiru (Jane), University of Ulster, UK
- Zhu, Michelle M., Montclair State University, USA
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- View Author guidelines.
Deep learning COVID-19 diagnosis
22 March, 2022
COVID-19 remains a significant challenge the world over. Research in the International Journal of Computational Biology and Drug Design, discusses how X-ray images and CT (computerised tomography) scans can reveal much about the effects of the disease on a patient's lungs. However, the use of convolutional neural networks (CNN) can now be used to improve detection of the disease. The standard tests for COVID-19 with which the general public have become rather familiar during the last two years – the so-called lateral flow antigen tests (LFT) and reverse transcriptase polymerase chain reaction (PCR) tests – have many several pros and cons. The LFT system was quickly developed into a portable test, not dissimilar to a pregnancy test kit [...]More details...
The drug war on COVID-19
23 March, 2022
While vaccination and public education concerning the transmission of the coronavirus causing COVID-19 have been at the forefront of our response to the pandemic, there remains an urgent need for pharmaceutical interventions in cases where infection occurs and leads to severe morbidity with a significant risk of death. New work in the International Journal of Computational Biology and Drug Design has focused on three protein targets in the body that are thought to be critical to the propagation of the virus in the body following infection and lead to symptoms. According to Srija Mukherjee and Santanu Paul of the Laboratory of Cell and Molecular Biology at the University of Calcutta, India, angiotensin-converting enzyme-2 receptor (ACE-2) represents a promising target for small molecule pharmaceuticals. SARS-CoV2 enters human cells via the ACE-2 receptor located in the membrane of lungs, arteries, kidneys, and intestine. As such, a small molecule that selectively targets this protein could be used to reduce the interaction of the virus with those proteins and so impede its cycle of infection to replication [...]More details...