Journal of Biochemical Technology

ISSN: 0974-2328
DOI Prefix: 10.51847

Welcome to the Journal of Biochemical Technology, a prestigious international double-blind peer-reviewed journal dedicated to advancing excellence in biochemical, biotechnological, and bioinformatics research with direct applications in biology and medicine. We are committed to maintaining the highest standards of scientific integrity, providing authors with a trusted platform to publish high-quality, impactful research. Our quarterly publication schedule ensures the timely dissemination of important discoveries, promoting the exchange of innovative ideas and developments among researchers worldwide.
Focusing on critical areas such as enzymatic mechanisms, protein engineering, molecular genetics, medical biotechnology, computational biology, genomics, and proteomics, our journal serves as a specialized platform for researchers working at the intersection of biochemistry and biotechnology. The journal is particularly interested in research with biomedical and therapeutic applications, including drug discovery, gene therapy, and cancer research.
Our dedicated editorial team offers full support throughout the submission and publication process, providing guidance on experimental design, data analysis, formatting, and submission procedures. We invite researchers, scholars, and practitioners to contribute to the advancement of biochemical technology, as we collectively work toward solving complex medical and scientific challenges. Our archiving policy includes both the publisher and a secondary database.

Publication Schedule: Quarterly (4 issues per year).

Announcement and Advertisement 
Announcements regarding scientific activities such as conferences, symposium, are published for free. Advertisements can be either published or placed on website as banners.

 

Publisher:

Deniz Publication
Guzelyali Mah. Sahilyolu Cad.Defne Sok. No: 7, 34903 Pendik, Istanbul, Turkey.

Email: [email protected]

Tell: +905344990778

Latest Articles
Diagnosis of Neonatal Brain Pathologies: Analysis of the Effectiveness of Deep Learning Algorithms and Expert Evaluation
Diagnosis of Neonatal Brain Pathologies: Analysis of the Effectiveness of Deep Learning Algorithms and Expert Evaluation
Written by Arina Railievna Krasnoshchekova   Published on Issue 4 Vol 16, 2025
The purpose of this scientific work is to conduct a comparative analysis of the diagnostic effectiveness, time, and economic indicators of deep learning algorithms and expert assessment in the diagnosis of brain development abnormalities in newborns according to neuroimaging data from the UNICEF BIGH dataset. In a retrospective study, 300 ultrasound and MRI scans were used. Each case was independently analyzed by the U-Net segmentation model, the EfficientNet classification model, a group of und Read More

Dual Antagonism of FGF2 and CSF1 by Computationally Designed Peptide-Ligand Conjugates for Targeted Glioblastoma Therapy
Dual Antagonism of FGF2 and CSF1 by Computationally Designed Peptide-Ligand Conjugates for Targeted Glioblastoma Therapy
Written by Haitham Al-Madhagi   Published on Issue 4 Vol 16, 2025
The cold brain tumor glioblastoma is one of the aggressive cancers that display infiltrative cells and chemoresistance. The reference treatment with Temozolamide unveiled a significant survival rate, while the specific targeted therapy, such as monoclonal antibodies, is hindered by impermeability through the blood-brain barrier. The present study aims to utilize the pharmacology of peptide-ligand conjugates (PLC) as a preferable targeted option for such a complex type of cancer. GGKRPAR and RPAR Read More

In Silico Development of a Multi-Epitope Vaccine Using Advanced Bioinformatics Tools and Techniques
In Silico Development of a Multi-Epitope Vaccine Using Advanced Bioinformatics Tools and Techniques
Written by Thamoghna Sure   Published on Issue 4 Vol 16, 2025
The rapid global spread and impact of SARS-CoV-2 and other emerging infectious diseases highlight the urgent need for the swift development of effective vaccines. Traditional vaccine production processes are time-consuming and resource-intensive. The present study focused on an in-silico strategy combined with sophisticated bioinformatics tools to develop a multi-epitope vaccine candidate against the SARS-CoV-2 membrane glycoprotein. The full SARS-CoV-2 genome was downloaded from NCBI to determi Read More

Metabolic Dysregulation in Women with Unexplained Infertility and Pregnancy Loss
Metabolic Dysregulation in Women with Unexplained Infertility and Pregnancy Loss
Written by Anastasia Evgenievna Verstova   Published on Issue 4 Vol 16, 2025
This prospective cohort study investigates the association between metabolic disturbances and reproductive dysfunction in women with idiopathic infertility and recurrent pregnancy loss (RPL). Conducted at the Perinatal Centre of Grozny from 2022 to 2025, the study involved 240 women allocated into three groups: Group 1 (n=120) with idiopathic infertility/RPL, Group 2 (n=60) with tubal factor infertility, and a control Group 3 (n=60) of fertile women. All participants underwent a comprehensive as Read More

Issue 1 Volume 17 - 2026