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Journal Photo for Computers in Biology and Medicine
Peer reviewed only Open Access

Computers in Biology and Medicine (CBM)

Publisher : Elsevier BV
Biomedical Biology Medicine
Claim Your Journal Get PRC Visit Website
e-ISSN 1879-0534
p-ISSN 0010-4825
Issue Frequency Monthly
Impact Factor 7.0
Est. Year 1970
Mobile 441865610674
Language English
APC YES
Impact Factor Assignee Google Scholar
Email l.brett@elsevier.com

Journal Descriptions

Computers in Biology and Medicine, a companion title to Informatics in Medicine Unlocked, is a medium of international communication of the revolutionary advances being made in the application of the computer to the fields of bioscience and medicine. Articles which examine the following topics of special interest are being featured in Computers in Biology and Medicine: Computer aids to the analysis of biochemical systems, computer aids to biocontrol-systems engineering, neuronal simulation by digital-computer gating components, automatic computer analysis of pictures of biological and medical importance, use of computers by commercial pharmaceutical and chemical organizations, radiation-dosage computers, and accumulating and recalling individual medical records, real-time languages, interfaces to patient monitors, clinical chemistry equipment, data handling and display in nuclear medicine and therapy.

Computers in Biology and Medicine (CBM) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Biomedical, Biology, Medicine, Data Processing, Bioinformatics, Computer Science Applications, Health Informatics , Online or Print , Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN P-ISSN: 0010-4825, E-ISSN: 1879-0534, Established: 1970, Impact Factor: 7.0
  • Does Not Provide Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing

Publications of CBM

NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides
Mohammad Ali Moni September, 2022
Tumor homing peptides (THPs) play a crucial role in recognizing and specifically binding to cancer cells. Although experimental approaches can facilitate the precise identification of THPs, ...
Bioinformatics and system biology approaches to identify pathophysiological impact of COVID-19 to the progression and severity of neurological disease...
Mohammad Ali Moni November, 2021
The Coronavirus Disease 2019 (COVID-19) still tends to propagate and increase the occurrence of COVID-19 across the globe. The clinical and epidemiological analyses indicate the link between...
rMisbeta: A robust missing value imputation approach in transcriptomics and metabolomics data
Mohammad Ali Moni November, 2021
Transcriptomics and metabolomics data often contain missing values or outliers due to limitations of the data acquisition techniques. Most of the statistical methods require complete dataset...
Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection
Mohammad Ali Moni November, 2021
The coronavirus disease 2019 (COVID-19) is caused by the infection of highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as the novel coronavirus. In ...
LungNet: A hybrid deep-CNN model for lung cancer diagnosis using CT and wearable sensor-based medical IoT data
Mohammad Ali Moni December, 2021
Lung cancer, also known as pulmonary cancer, is one of the deadliest cancers, but yet curable if detected at the early stage. At present, the ambiguous features of the lung cancer nodule mak...
Machine learning-based statistical analysis for early stage detection of cervical cancer
Mohammad Ali Moni December, 2021
Cervical cancer (CC) is the most common type of cancer in women and remains a significant cause of mortality, particularly in less developed countries, although it can be effectively treated...
A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images
Mohammad Ali Moni December, 2021
Coronavirus disease-19 (COVID-19) is a severe respiratory viral disease first reported in late 2019 that has spread worldwide. Although some wealthy countries have made significant progress ...
DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins
Mohammad Ali Moni June, 2022
Accurate identification of DNA-binding proteins (DBPs) is critical for both understanding protein function and drug design. DBPs also play essential roles in different kinds of biological ac...
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins
Mohammad Ali Moni July, 2022
Thermophilic proteins (TPPs) are important in the field of protein biochemistry and development of new enzymes. Thus, computational methods must be urgently developed to accurately and rapid...
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides
Mohammad Ali Moni September, 2022
Tumor homing peptides (THPs) play a crucial role in recognizing and specifically binding to cancer cells. Although experimental approaches can facilitate the precise identification of THPs, ...