All articles
46 articles
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Leveraging Genome-Wide Association Studies for Precision Medicine in Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) are the leading cause of death globally, with complex etiologies involving genetic, environmental, and lifestyle factors. Genome-wide association studies (GWAS) have significantly advanced the understanding of genetic underpinnings of CVDs by identifying numerous risk loci and variants associated with various cardiovascular conditions. This review explores the potential of GWAS to drive precision medicine in cardiovascular diseases by linking genetic data with clinical outcomes, providing insights into disease …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 35–39 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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Comparative Proteomics: From Cell Lines to Clinical Samples
Abstract: Comparative proteomics is a powerful tool for understanding the molecular differences between various biological samples. It entails identifying and measuring proteins in complex biological samples to assess their abundance, modifications, and interactions under various conditions. This approach plays a crucial role in advancing biomedical research, especially in disease understanding, biomarker discovery, and therapeutic development. While cell lines are widely used for proteomic studies due to their controlled environments and reproducibility, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 30–34 Read article
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Neuroinformatics and Its Impact on the Future of Brain-Computer Interface Technology
Abstract: Neuroinformatics, a multidisciplinary field combining neuroscience, information technology, and data science, plays a crucial role in advancing brain-computer interface (BCI) technology. By leveraging large-scale neural data, machine learning algorithms, and computational models, neuroinformatics enhances our understanding of brain function and improves the design and development of BCIs. The integration of neuroinformatics into BCI systems offers new possibilities for interpreting complex brain signals, facilitating real-time communication between the brain and external …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 9–18 Read article
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Data Integration and Visualization in Bioinformatics: Techniques and Challenges
Abstract: Data integration and visualization play essential roles in bioinformatics, facilitating the thorough analysis, and interpretation of intricate biological datasets. In the field of bioinformatics, vast amounts of data are generated from various experimental platforms, such as genomic sequencing, proteomics, transcriptomics, and metabolomics. However, the heterogeneity of these datasets, coupled with their large scale and complexity, presents significant challenges in terms of integration, analysis, and visualization. Data integration techniques aim to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Computational Biomodeling: Transforming Drug Design with Advanced Simulations
Abstract: Computational biomodeling has emerged as a transformative approach in the field of drug discovery, significantly enhancing the efficiency and precision of identifying and optimizing potential drug candidates. This article explores the various computational techniques utilized in drug design, including molecular docking, molecular dynamics (MD) simulations, free energy calculations, and virtual screening, and examines how these methods collectively contribute to the drug development process. The integration of these advanced simulations allows …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 24–29 Read article
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Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
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Exploring the Potential of Allium sativum Phytocompounds as B-Cell Leukemia 2 Inhibitors in Acute Lymphoblastic Leukemia: Molecular Docking Study
Abstract: Objective: Acute lymphoblastic leukemia (ALL) is a lymphoid progenitor cell malignancy that could be treated with plant-based drugs, thus alleviating the off-target effects caused by conventional chemotherapy. Since ancient days, Allium sativum has been an integral part of traditional medicine and an excellent antimicrobial, antioxidant, and antiproliferative agent. Hence, this study aims to assess the anti-leukemic potential of A. sativum phytoconstituents as the B-cell leukemia 2 protein (Bcl-2) natural inhibitor …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 53–80 Read article
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Targeting Vasopressin 2 Receptor (V2R) in Renal Cystogenesis by Exploring the Nephroprotective Potential of “Terminalia arjuna”
Abstract: Objectives: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder, leading to the formation of multiple cysts in the kidneys. It is a major cause of end-stage renal disease (ESRD), which often requires dialysis or a kidney transplant for survival. This research focuses on identifying potential bioactive compounds derived from natural sources that show promise for drug development targeting the V2R gene. Methods: The naturally occurred …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 14–24 Read article
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Computational Investigation of Withania somnifera Compounds Targeting S. pombe SMN YG-Dimer in Spinal Muscular Atrophy: Insights from Molecular Docking Analysis
Abstract: Objectives: The primary objective of this study is to determine the potential of phytochemical constituents of Withania somnifera in treating spinal muscular atrophy, an autosomal recessive genetic neurodegenerative disorder, through computational techniques. To investigate the binding affinity of phytocompound to the target protein S. pombe SMN YG-Dimer through molecular docking. Besides, evaluating the pharmacological attributes of phytochemical constituents to assess their ability as an ideal prospect for developing therapeutic medication. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 39–52 Read article
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In Silico Molecular Docking Studies of Phytocompounds from Melissa officinalis Against MPXV Poxin Target
Abstract: Objectives: This study aimed to evaluate the inhibitory potential of phytocompounds of Melissa officinalis against the MPXV poxin protein target, a key virulence factor in monkeypox infection. Methods: Molecular docking performed using PyRx, a virtual screening software, was conducted to predict the binding affinities of the compounds to MPXV poxin. Prior to docking, the compounds were subjected to comprehensive analysis, including Lipinski's rule of five, evaluation of physicochemical properties, pharmacological …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 25–38 Read article
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In Silico Analysis and Docking Study of the Active Phytocompounds of Bacopa monnieri Against Alzheimer Disease
Abstract: Objective: Alzheimer’s is a neurodegenerative disease and is the cause of 60–70% of cases of dementia. It infected a million people worldwide. An effort was undertaken to explore the potential of natural compounds found in Bacopa monnieri, a plant renowned for its extensive medicinal properties in Indian Ayurveda, to combat the disease. This was achieved through molecular docking studies, evaluation of drug-likeness, and comprehensive ADME (absorption, distribution, metabolism, and excretion) …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 1–13 Read article
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Unveiling Nature’s Potential: In Silico Exploration and Identification of Herbal Remedies for Major Depressive Disorder Through Molecular Interaction Studies
Abstract: Major depressive disorder (MDD), a globally discussed mental health condition, has drawn significant attention because of its unique and intricate nature. This is marked by the enduring presence of negative emotions stemming from a lack of interest, diminished self-esteem, and excessive rumination. Despite the widespread availability of various antidepressant medications, their effectiveness is hindered by low response rates, prolonged treatment durations, and the prevalence of side effects, such as headaches, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 54–62 Read article
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Computational Screening of Vitex negundo Compounds for Potential Arthritis Therapies in India
Abstract: Objective: Arthritis is a pervasive medical condition that manifests as inflammation and discomfort within the joints. As of September 2021, arthritis has affected an estimated 180 million people in India, making it a substantial public health concern with a considerable impact on individuals' quality of life and healthcare systems. Therefore, using molecular docking, drug-likeness prediction, and ADME analysis, an effort was made to identify natural compounds from Vitex negundo, which …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 01–18 Read article
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In Situ Investigation of Hemidesmus indicus Phytocompound Extracts as a Therapeutic Target for Acute Myeloid Leukemia
Abstract: Objective: Acute myeloid leukemia (AML) is an apoptotic condition in the hematopoietic system induced by the differentiation and maturation of stem cells into erythrocytes, and leukemic cell proliferation is suppressed as the PI3K-Akt-mTOR pathway is pharmacologically targeted with certain inhibitors. As a result, in silico molecular docking of compounds against AML receptors, CTMP, was used in computational research on Hemidesmus indicus to uncover therapeutic phytochemicals for AML. Thus, this study …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 38–53 Read article
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In Silico Investigation of 2,3-Dihydrobenzofuran from Centella asiatica: A Possible Pioneer in the Management of Tetanus
Abstract: Objective: Tetanus toxin (TeNT) is a neuroprotein toxin, the most toxic known. They have three functional domains and are structurally similar. They possess an N-terminal catalytic section (light chain), an internal domain for heavy-chain translocation (HN domain), and a C-terminal receptor binding domain for the heavy chain (Hc domain or RBD). Tetanus, an acute nerve-affecting disease, is provoked by a toxin-producing bacterium called Clostridium tetani. This bacterium is environmental, Gram-positive, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 19–30 Read article
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Computational Exploration of Bhrijraj-derived Phytochemicals as Potential Anti-inflammatory Agents: A Molecular Docking Study with Cyclooxygenase-II Complex
Abstract: The molecular docking analysis was meticulously conducted using state-of-the-art computational tools, notably Chimera and Python. These tools were employed to unravel the complex interactions between the identified phytochemicals from Bhrijraj and the target protein, COX-II. The 3D structures of the phytochemicals were prepared with precision using ChemSketch, ensuring accuracy in the subsequent molecular docking simulations. This rigorous approach enhances the reliability and validity of the findings. This research aims to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 31–37 Read article