All articles
38 articles
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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
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Computational and Molecular Aspects of DNA Profiling in Forensic and Biomedical Sciences
Abstract: DNA profiling has changed many diverse modern sectors, from health and criminal justice to ancestry research and animal conservation. It is one of the most important scientific instruments of our time. This technique makes it possible to identify people, analyze family relationships, and learn more about biology by looking at unique genetic markers in a person’s DNA. DNA profiling has changed the way forensic science works by making it easier …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 14–18 Read article
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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Identification of Hub Genes and Enriched Gene Ontology & Pathways in Idiopathic Pulmonary Fibrosis Through Bioinformatics Approaches
Abstract: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease marked by aberrant remodeling of lung tissue and excessive extracellular matrix deposition, ultimately leading to respiratory failure. Despite ongoing research, the molecular mechanisms underlying IPF remain incompletely understood. This research aims to uncover differentially expressed genes (DEGs) and related biological pathways through an integrated analysis of microarray data. Two publicly available datasets, GSE110147 and GSE53845, were obtained from the Gene …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 1–13 Read article
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Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133
Abstract: Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental disorder characterized by difficulties in social interaction, communication impairments, and restricted or repetitive patterns of behavior. Despite its increasing prevalence, the underlying molecular mechanisms remain poorly understood. Advances in transcriptomics offer opportunities to investigate the gene expression changes that may contribute to ASD pathophysiology. In this study, the microarray dataset GSE42133 was analyzed, which comprises gene expression profiles from peripheral blood samples …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 37–48 Read article
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Revolutionizing Vaccine Development:The Transformative Role of Bioinformatics in Designing Next-Generation Immunotherapies
Abstract: Vaccines have long been central to the prevention and control of infectious diseases, dramatically reducing morbidity and mortality worldwide. In the modern era, the integration of bioinformatics has revolutionized vaccine development by enabling rapid, precise, and cost-effective identification of potential vaccine targets. This seminar explores the multifaceted applications of bioinformatics in vaccinology, including antigen discovery, epitope prediction, structural modeling, molecular docking, and immunoinformatics-driven vaccine design. Special emphasis is placed on …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 19–33 Read article
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Braegen Monitor: Virtual Diagnosis And Home Training For Children With Cognitive Disabilities
Abstract: Braegen Monitor is an innovative software solution designed to support children with cognitive disabilities by providing personalized home-training and engagement activities. The platform enables caretakers to submit EEG reports through the app, which are then virtually analyzed by a child psychiatrist. This ensures timely and professional diagnosis without the stress of frequent hospital visits. A unique feature of Braegen Monitor is the psychiatrist’s personal interview with the caretaker or parent …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 44–54 Read article
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Cardiovascular Modeling with Computational and Mathematical Methods
Abstract: The cardiovascular system, a complex network responsible for delivering life-sustaining oxygen and nutrients throughout the body, is a prime target for advanced understanding and improved therapies. Due to the inherent difficulties in directly observing internal physiological processes and the complexities of interactions within the system, computational and mathematical modeling have emerged as powerful tools in cardiovascular research. This article explores the significance of these methods in unveiling the heart's secrets …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 11–21 Read article
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A Correlational Analytical Study on Smartphone Usage, Physical Activity & Sleep Quality Among Health Science Students
Abstract: Physical activity refers to any bodily movement generated by skeletal muscles that results in the use of energy. It is considered risk factor for various cardiovascular disease leading to higher mortality and morbidity. Sleep is naturally occurring condition marked by a change in consciousness, a significant reduction in sensory activity and the suppression of most voluntary movements. Technological advancements over the past two decades have resulted in rise in smartphone …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 22–32 Read article
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Screening of Pharmaceutically Significant Methioninase-Producing Fungi from the Satpura Range of Hoshangabad District and Its Large-Scale Production
Abstract: L-methioninase, an enzyme with notable anticancer properties, has emerged as a promising therapeutic agent due to its ability to selectively degrade methionine, a critical amino acid for the survival of methionine-dependent cancer cells. Methionine dependency, observed in many tumor cells, is a metabolic vulnerability that can be exploited for targeted cancer therapy. The Satpura Range in the Narmadapuram District, India, with its diverse microbial ecosystems, offers a rich reservoir for …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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AI: Revolutionizing Pharmacy Practice and Enhancing Patient Care and Safety
Abstract: The use of artificial intelligence (AI) in pharmacy is transforming medication management, improving patient care, and boosting safety. By leveraging cutting-edge technologies, such as machine learning, natural language processing, and predictive analytics, AI enables pharmacists to develop personalized treatment plans and anticipate possible adverse drug reactions. AI-driven systems enhance operational efficiency by streamlining inventory management, prescription processing, and administrative duties, allowing pharmacists to devote more time to patient care. Additionally, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 13–20 Read article
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AI Activity to Enhance Productivity, Creativity, and Sustainable Development of AI in Healthcare
Abstract: The application of artificial intelligence (AI) in healthcare is revolutionizing the industry by fostering both productivity and creative approaches to patient care and medical research. This study explores how artificial intelligence (AI) is reshaping healthcare by streamlining workflows, improving diagnostic precision, and supporting personalized treatment plans. AI-powered technologies are reshaping the way medical professionals approach patient care, providing tools that not only automate routine administrative and clinical tasks but also …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 21–29 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article