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15 articles for “Drug Prediction”
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Research ArticleOpen accessEvery word in the titleA Drug-Target Interaction Prediction Based on Supervised Probabilistic ClassificationManmohan Singh, Susheel Kumar Tiwari, G. Swapna et al.Bayesian ranking-based drug-target relationship prediction has achieved good results, but it ignores the relationship between drugs of the same target. A new method is proposed for drug-target relationship prediction based on groups by Appling Bayesian. According to the reality that drugs interacting with a specific target have similarities, a grouping strategy was introduced to make these similar drugs interact. A … …Journal of Computer Science, Vol. 19, Issue 10 · 1 Sep 2023 · 5,454 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleProposal for the Development of Adverse Drug Reaction Prediction ModelMuaed J. Alomar, Anas A. Hourani, Syed A. SulaimanInformation technology, which uses the computer for data processing and decision-making, has invaded all kinds of sciences. Health informatics is one of these important areas. The Objective of this study is to develop a mathematical model that calculates the percentage of ADR occurrence using the data available from primary literature for a specific medication. A mathematical model was developed to … …American Journal of Pharmacology and Toxicology, Vol. 3, Issue 2 · 30 Jun 2008 · 7,394 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Analysis of Drug Reviews: Identifying Patient Conditions, Predicting Drug Ratings, and Sentiment AnalysisRafat Hammad, Mohammad Ashraf Ottom, Ayah Bani BakerUnderstanding patients' experiences with medications is essential for improving drug effectiveness, detecting potential side effects, and enhancing overall patient satisfaction. This research investigates applying machine learning to patient drug reviews across three main tasks: Identifying patient conditions, predicting drug ratings, and performing sentiment analysis. We implemented and evaluated Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Recurrent Neural Networks … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 736 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Framework to Predict the Strength of New SMILE Using Graph Attention NetworkSandhi Kranthi Reddy, S. V. G. ReddyMachine Learning (ML) and Deep Learning (DL) have significantly advanced various fields, including healthcare, finance, autonomous systems, and scientific research. In healthcare, these technologies have been widely applied to disease prediction, such as cancer and diabetes. However, the challenge of drug resistance persists, creating a need for more effective drugs. Developing new drugs is a complex, expensive, and time-intensive process, … …Journal of Computer Science, Vol. 21, Issue 10 · 25 Nov 2025 · 2,157 accessesView PDFCite
Research ArticleOpen accessIn the abstractSemSimp: A Parametric Method for Evaluating the Semantic Similarity of Digital ResourcesAntonio De Nicola, Anna Formica, Ida Mele, Francesco TaglinoAbioui, H., Idarrou, A., Bouzit, A., & Mammass, D. (2018). Towards a Novel and Generic Approach for OWL Ontology Weighting. Procedia Computer Science, 127, 426–435. https://doi.org/10.1016/j.procs.2018.01.140 Adhikari, A., Dutta, B., Dutta, A., Mondal, D., & Singh, S. (2018). An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology. Journal of the Association for … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,773 accessesView PDFCite
Research ArticleOpen accessIn the abstractVirtual Screening of CPP Conjugated Peptide as QcrB BCC Protein Inhibitors of Mycobacterium tuberculosis BacteriaMuhammad Ihsan Muttaqin, Manaman Huang, Usman Sumo Friend TambunanTuberculosis is a global leading cause of death, just below COVID-19 and ranked above HIV. This disease is caused by a pathogen called Mycobacterium tuberculosis, which spreads easily through the air and is known to remain latent in most people's bodies, about a quarter of the world's population. The current problems with TB also include two main concerns: The official … …OnLine Journal of Biological Sciences, Vol. 24, Issue 3 · 14 Mar 2024 · 5,518 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Microbe-Drug Association based on Similarity and Semi-Supervised LearningLingzhi Zhu, Jun Wang, Guixiang Li et al.Increasing clinic evidences have showed that microbial communities play important roles in human health and disease. Predicting hidden microbe-drug associations can be helpful in understanding the microbe-drug association mechanisms in clinical treatment, drug discovery, combinations and repositioning. Some computational methods were proposed to predict the associations of microbes and drugs. However, the prediction performance of these methods needs to be … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 9 Mar 2021 · 7,535 accessesView PDFCite
Review ArticleOpen accessIn the abstractProtein Sequences Features Extraction for Predicting Beta- Turns and their Types: A ReviewMurtada Khalafallah Elbashir ElfakiBeta-turns are considered to be important secondary structure types that have essential role in molecular recognition, protein folding and stability. They represent 25% of protein structures, therefore they are the most common type of non-repetitive or tight turns structures. Their prediction is considered to be an important issue in bioinformatics and molecular biology, because it provides valuable information and inputs … …Journal of Computer Science, Vol. 15, Issue 9 · 1 Oct 2019 · 7,694 accessesView PDFCite
Research ArticleOpen accessIn the abstractKRLSMDA: Identifying Human miRNA–Disease Association Based on Similarity and Kronecker Regularized Least Squares MethodLingzhi Zhu, Weimin Gao, Guixiang Li et al.A growing number of studies have suggested that miRNAs (microRNAs) have associations with human diseases, the design and discovery of drug. But so far, we do not yet fully understand the molecular mechanism of miRNAs in the development of human diseases. Predicting miRNA-disease associations is helpful for understanding the molecular mechanism of miRNAs in the development of human diseases. However, … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 15 Mar 2021 · 6,403 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Construction of Two and Three Dimensional Molecular Models for the miR-31 and Its Silencer as the Triple Negative Breast Cancer BiomarkersArli Aditya ParikesitThe Triple Negative Breast Cancer (TNBC) is considered as the most difficult Breast Cancer type to be medicated. So far, the acceptable medication and diagnostics measure are based upon the proteomics-world view, especially with utilizing the natural products and their derivatives as drug candidates. However, as the transcriptomics-studies are getting more advanced, the research on non-coding (nc)RNA is being considered … …OnLine Journal of Biological Sciences, Vol. 18, Issue 4 · 18 Oct 2018 · 7,772 accessesView PDFCite