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Relevant bibliographies by topics / "A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS

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Academic literature on the topic '"A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS'

Author: Grafiati

Published: 9 March 2023

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Journal articles on the topic ""A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS"

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Pilehvar, Mohammad Taher, Adam Bernard, Damian Smedley, and Nigel Collier. "PheneBank: a literature-based database of phenotypes." Bioinformatics 38, no. 4 (2021): 1179–80. http://dx.doi.org/10.1093/bioinformatics/btab740.

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Abstract Motivation Significant effort has been spent by curators to create coding systems for phenotypes such as the Human Phenotype Ontology, as well as disease–phenotype annotations. We aim to support the discovery of literature-based phenotypes and integrate them into the knowledge discovery process. Results PheneBank is a Web-portal for retrieving human phenotype–disease associations that have been text-mined from the whole of Medline. Our approach exploits state-of-the-art machine learning for concept identification by utilizing an expert annotated rare disease corpus from the PMC Text M

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Cios, K. J., R. E. Freasier, L. S. Goodenday, and L. T. Andrews. "An expert system for diagnosis of coronary artery stenosis based on 201TI scintigrams using the Dempster-Shafer theory of evidence." Bioinformatics 6, no. 4 (1990): 333–42. http://dx.doi.org/10.1093/bioinformatics/6.4.333.

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Garrido, Oswgladys, and Elizabeth Ferrer. "Characterization of Three cDNAs Obtained by Spliced Leader-PCR Screening of a Taenia solium cDNA Library." Uniciencia 36, no. 1 (2022): 1–10. http://dx.doi.org/10.15359/ru.36-1.31.

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Cysticerci or metacestodes of Taenia solium cause cysticercosis, being the neurocysticercosis (NCC) the main pathology. The characterization of genes is essential for the knowledge of parasite biology, the understanding of the parasite-host relationship, and the identification of possible targets for diagnosis, treatment, and protection. The objective of this work was the molecular and bioinformatic characterization of three news cDNAs (TsTF10, TsAAP8, and TsrGAP8), obtained by spliced leader-PCR screening of a Taenia solium cDNA library. The sequences of the three cDNA were compared with the

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Mao, Shunfu, Yue Zhang, Georg Seelig, and Sreeram Kannan. "CellMeSH: probabilistic cell-type identification using indexed literature." Bioinformatics 38, no. 5 (2021): 1393–402. http://dx.doi.org/10.1093/bioinformatics/btab834.

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Abstract Motivation Single-cell RNA sequencing (scRNA-seq) is widely used for analyzing gene expression in multi-cellular systems and provides unprecedented access to cellular heterogeneity. scRNA-seq experiments aim to identify and quantify all cell types present in a sample. Measured single-cell transcriptomes are grouped by similarity and the resulting clusters are mapped to cell types based on cluster-specific gene expression patterns. While the process of generating clusters has become largely automated, annotation remains a laborious ad hoc effort that requires expert biological knowledg

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Alazmi, Meshari, Hiroyuki Kuwahara, Othman Soufan, Lizhong Ding, and Xin Gao. "Systematic selection of chemical fingerprint features improves the Gibbs energy prediction of biochemical reactions." Bioinformatics 35, no. 15 (2018): 2634–43. http://dx.doi.org/10.1093/bioinformatics/bty1035.

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Abstract Motivation Accurate and wide-ranging prediction of thermodynamic parameters for biochemical reactions can facilitate deeper insights into the workings and the design of metabolic systems. Results Here, we introduce a machine learning method with chemical fingerprint-based features for the prediction of the Gibbs free energy of biochemical reactions. From a large pool of 2D fingerprint-based features, this method systematically selects a small number of relevant ones and uses them to construct a regularized linear model. Since a manual selection of 2D structure-based features can be a

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Hu, Xiaotian, Cong Feng, Yincong Zhou, Andrew Harrison, and Ming Chen. "DeepTrio: a ternary prediction system for protein–protein interaction using mask multiple parallel convolutional neural networks." Bioinformatics 38, no. 3 (2021): 694–702. http://dx.doi.org/10.1093/bioinformatics/btab737.

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Abstract Motivation Protein–protein interaction (PPI), as a relative property, is determined by two binding proteins, which brings a great challenge to design an expert model with an unbiased learning architecture and a superior generalization performance. Additionally, few efforts have been made to allow PPI predictors to discriminate between relative properties and intrinsic properties. Results We present a sequence-based approach, DeepTrio, for PPI prediction using mask multiple parallel convolutional neural networks. Experimental evaluations show that DeepTrio achieves a better performance

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Sari, Indah Juwita, Pongprapan Pongsophon, Wanwipa Vongsangnak, Pattamaporn Pimthong, and Sasithep Pitiporntapin. "The development of molecular genetics concept test for senior high school students using Rasch analysis." International Journal of Evaluation and Research in Education (IJERE) 11, no. 4 (2022): 1687. http://dx.doi.org/10.11591/ijere.v11i4.21846.

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<span lang="EN-US">Developing a high-quality test item requires substantial time and effort. A well-developed item bank is conducted using rigorous development and validation procedures. This study aimed to describe the development process of molecular genetics concept test (MGCT) for senior high school students using Rasch analysis under <a name="_Hlk107307570"></a>Berkeley evaluation and assessment research (BEAR) assessment system framework. The test consists of 50 multiple-choice items to assess conceptual understanding of molecular genetics concepts. The MGCT was develop

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Edwards, Marion, and Roger E. Cooley. "Expertise in expert systems: knowledge acquisition for biological expert systems." Bioinformatics 9, no. 6 (1993): 657–65. http://dx.doi.org/10.1093/bioinformatics/9.6.657.

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Andruzzi, Luisa. "Application of liquid biopsy to uncover critical cancer insights using the GeneReader NGS system." Journal of Clinical Oncology 35, no. 15_suppl (2017): e13102-e13102. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e13102.

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e13102 Background: NGS studies of cancer are primarily based on studies of FFPE samples, the use of which is limited by surgical feasibility, tissue availability and patient preference. An emerging field of study is focused on circulating-free DNA (cfDNA), sometimes termed “Liquid Biopsy”. While holding great promise as the future of cancer understanding and management, the liquid biopsy field is still nascent, lacking an integrated NGS workflow solution with proven performance. Methods: QIAGEN is an established expert in the field of sample preparation for liquid biopsy. The combination of th

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Papageorgiou, L., H. Alkenaris, M. Zervou, D. Vlachakis, G. Goulielmos, and E. Eliopoulos. "POS0350 EPIONE APPLICATION: AN INTEGRATED GENOTYPE ANALYSIS WEB SERVER FOR CLINICAL GENOMICS IN SYSTEMIC LUPUS ERYTHEMATOSUS (SLE)." Annals of the Rheumatic Diseases 80, Suppl 1 (2021): 405. http://dx.doi.org/10.1136/annrheumdis-2021-eular.1496.

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Background:Genome wide association studies (GWAS) have successfully identified novel autoimmune disease-associated loci, with many of them shared by multiple disease-associated pathways but much of the genetics and pathophysiological mechanisms remain still obscure [1-3]. SLE is a chronic, highly heterogeneous autoimmune disease, characterized by differences in autoantibody profile, serum cytokines, and a multi-system involvement [4]. Epione Application is an integrated bioinformatics web-tool designed to assist medical experts and researchers in the process of diagnosing SLE [5].Objectives:To

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Dissertations / Theses on the topic ""A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS"

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Harley, Linda Rosemary. "The application of a knowledge based system to micro-electrode guided neurosurgery." Thesis, Available online, Georgia Institute of Technology, 2004, 2004. http://etd.gatech.edu/theses/available/etd-02042004-131540/unrestricted/harley%5Flinda%5Fr%5F200405%5Fms.pdf.

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Thesis (M. S.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2004.<br>Dr. Michael Hunter, Committee Member ; Dr. Alexander M. Puzrin, Committee Member ; Dr. Nelson Baker, Committee Chair. Includes bibliographical references.

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Aniba, Mohamed Radhouane. "Knowledge based expert system development in bioinformatics : applied to multiple sequence alignment of protein sequences." Strasbourg, 2010. https://publication-theses.unistra.fr/public/theses_doctorat/2010/ANIBA_Mohamed_Radhouane_2010.pdf.

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L'objectif de ce projet de thèse a été le développement d'un système expert afin de tester, évaluer et d'optimiser toutes les étapes de la construction et l'analyse d'un alignement multiple de séquences. Le nouveau système a été validé en utilisant des alignements de référence et apporte une nouvelle vision pour le développement de logiciels en bioinformatique: les systèmes experts basés sur la connaissance. L'architecture utilisée pour construire le système expert est très modulaire et flexible, permettant à AlexSys d'évoluer en même temps que de nouveaux algorithmes seront mis à disposition.

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Palil, Md Dan Md. "An ergonomics design knowledge based expert system." Thesis, Loughborough University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321264.

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Millette, Lucien. "Improving the Knowledge-Based Expert System Lifecycle." UNF Digital Commons, 2012. http://digitalcommons.unf.edu/etd/407.

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Knowledge-based expert systems are used to enhance and automate manual processes through the use of a knowledge base and modern computing power. The traditional methodology for creating knowledge-based expert systems has many commonly encountered issues that can prevent successful implementations. Complications during the knowledge acquisition phase can prevent a knowledge-based expert system from functioning properly. Furthermore, the time and resources required to maintain a knowledge-based expert system once implemented can become problematic. There are several concepts that can be integrat

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Smith, Lyndon Neal. "A knowledge based system for powder metallurgy technology." Thesis, University of the West of England, Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364080.

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Middaugh, Regina A. "A knowledge based expert system for analyzing welded structures." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36013.

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Adams, Phillip M. "An Interactive Expert System Based Dialogue Manager( An Expert System's Quest For Knowledge)." NSUWorks, 1987. http://nsuworks.nova.edu/gscis_etd/380.

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Cooper, Robert D. "A knowledge-based system for hominid fossils." [Gainesville, Fla.] : University of Florida, 2004. http://purl.fcla.edu/fcla/etd/UFE0004420.

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Newcomb, Philip H. "The Knowledge Integration Tool : a knowledge based system development environment." Virtual Press, 1988. http://liblink.bsu.edu/uhtbin/catkey/546143.

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The current generation of conventional software productivity tools is likely to achieve at most a factor of two reduction in life-cycle costs by the early 1990s. With projected order of magnitude increases in system complexity and size, a far greater improvement (factor of 10 or higher) is needed. Significant cost reductions and qualitative improvements for many kinds of applications can be demonstrated by means of a knowledge-based integrated tool environment that both adheres to the software development standards of the software development organization and promotes rapid development of high

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Hussain, Tanveer. "A knowledge-based expert system for the dyeing of cotton." Thesis, Heriot-Watt University, 2004. http://hdl.handle.net/10399/206.

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Books on the topic ""A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS"

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library, Wiley online, ed. Knowledge based bioinformatics: From analysis to interpretation. John Wiley & Sons, 2010.

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Sadeghian, Ali Reza. A knowledge-based expert system for inductor design. National Library of Canada, 1993.

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A, Buckland John, and Wiig Karl M, eds. Planning for knowledge-based systems. Chantico Pub. Co., 1988.

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Center, Langley Research, ed. Knowledge-based system for flight information management. National Aeronautics and Space Administration, Langley Research Center, 1990.

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Center, Langley Research, ed. Knowledge-based system for flight information management. National Aeronautics and Space Administration, Langley Research Center, 1990.

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Jozefczyk, Jerzy. Knowledge-based intelligent system advancements: Systemic and cybernetic approaches. Information Science Reference, 2011.

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Designing knowledge-based systems. Prentice-Hall, 1986.

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Designing knowledge-based systems. Kogan Page, 1985.

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Jens, Pohl, ed. Knowledge-based CAAD and the CLIPS expert system shell. California Polytechnic State University, School of Architecture and Environment Design, CAD Research Unit, 1990.

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Mockler, R. J. Developing knowledge-based systems using an expert system shell. Macmillan Pub. Co., 1992.

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Book chapters on the topic ""A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS"

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Sharma, Anurag, Hitesh Marwaha, Vikrant Sharma, and Love Kumar. "An Artificial Intelligence-based Expert System for the Initial Screening of COVID-19." In Advanced AI Techniques and Applications in Bioinformatics. CRC Press, 2021. http://dx.doi.org/10.1201/9781003126164-1.

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Singh, Rajesh, Anita Gehlot, Mahesh Kumar Prajapat, and Bhupendra Singh. "Knowledge Based Expert System." In Artificial Intelligence in Agriculture. CRC Press, 2021. http://dx.doi.org/10.1201/9781003245759-7.

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Frydenberg, Mark, and Stephen I. Gallant. "Fuzziness and expert system generation." In Uncertainty in Knowledge-Based Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-18579-8_12.

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Chang, Kai-Hsiung, and William G. Wee. "A Knowledge-Based Mechanical Assembly Planning System." In Expert Systems in Engineering Applications. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84048-7_15.

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von Martial, Frank, Frank Victor, and Hiroshi Ishii. "A System for Knowledge-Based Information Extraction." In Database and Expert Systems Applications. Springer Vienna, 1990. http://dx.doi.org/10.1007/978-3-7091-7553-8_80.

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Eckardt, M., U. Ruch, and M. Schnabel. "Knowledge Based System for Diagnosing Anemia." In Expert Systems and Decision Support in Medicine. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-48706-4_93.

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Mitchell, A. A. "The Development of a Knowledge Based Media Planning System." In Data, Expert Knowledge and Decisions. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73489-2_7.

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Hudson, D. L., and M. E. Cohen. "Management of uncertainty in a medical expert system." In Uncertainty in Knowledge-Based Systems. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-18579-8_28.

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Taranath, N. L., B. P. Aniruddha Prabhu, Rakesh Dani, Devesh Tiwari, and L. M. Darshan. "Non-knowledge Based Decision Support System." In Proceedings of Third International Conference on Sustainable Expert Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7874-6_29.

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Yang, Tao, Jiao Feng, Jie Chen, Chunyan Dong, Youqun Shi, and Ran Tao. "A Clothing Recommendation System Based on Expert Knowledge." In Artificial Intelligence on Fashion and Textiles. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99695-0_1.

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Conference papers on the topic ""A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS"

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Biyouki, S. Amrollahi, I. B. Turksen, and M. H. Fazel Zarandi. "Fuzzy rule-based expert system for diagnosis of thyroid disease." In 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2015. http://dx.doi.org/10.1109/cibcb.2015.7300333.

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Pugalendhi, GaneshKumar, and Ku-Jin Kim. "Intelligent F-information for genetic swarm algorithm based fuzzy expert system." In BCB '15: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine. ACM, 2015. http://dx.doi.org/10.1145/2808719.2811414.

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Jiancheng, He, Li Xiaoqian Hong Fang Ding Hongjuan, Cao Xuebin, and Hu Yuanhui. "Development of the Cardiac failure expert system for Chinese medicine diagnosis based on database." In 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2013. http://dx.doi.org/10.1109/bibm.2013.6732639.

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Rahman, Md Mahmudur, Prabir Bhattacharya, and Bipin C. Desai. "A multiple expert-based melanoma recognition system for dermoscopic images of pigmented skin lesions." In 2008 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE). IEEE, 2008. http://dx.doi.org/10.1109/bibe.2008.4696799.

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Ahmad, Anees. "Knowledge-based expert system for optomechanical design." In Optical Science, Engineering and Instrumentation '97, edited by Robert E. Fischer, R. Barry Johnson, Richard C. Juergens, Warren J. Smith, and Paul R. Yoder, Jr. SPIE, 1997. http://dx.doi.org/10.1117/12.284050.

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Spence, A. R. "Bloom and Billet Mill expert system." In IEE Colloquium on Real-Time Knowledge Based Systems. IEE, 1995. http://dx.doi.org/10.1049/ic:19950110.

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Huang, Xin, Xuejiao Tang, Wenbin Zhang, et al. "A Generic Knowledge Based Medical Diagnosis Expert System." In iiWAS2021: The 23rd International Conference on Information Integration and Web Intelligence. ACM, 2021. http://dx.doi.org/10.1145/3487664.3487728.

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Chaudhury, Sriram, Ankitha Rao, and Dipti M. Sharma. "Anusaaraka: An expert system based machine translation system." In 2010 International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE). IEEE, 2010. http://dx.doi.org/10.1109/nlpke.2010.5587789.

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Soor, Prajyot, and Jayshree Ghorpade-Aher. "Expert search based knowledge sharing system for collaborative environment." In 2017 International Conference on Emerging Trends & Innovation in ICT (ICEI). IEEE, 2017. http://dx.doi.org/10.1109/etiict.2017.7977011.

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Wang, Tianshu, Ren Yu, Qiao Peng, Di Wang, and Xiaosen Song. "A fault diagnosis expert system based on knowledge matrix." In International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), edited by Shi-Jinn Horng. SPIE, 2022. http://dx.doi.org/10.1117/12.2661211.

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Reports on the topic ""A KNOWLEDGE-BASED EXPERT SYSTEM IN BIOINFORMATICS"

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Stunder, Mark J., Robert C. Koch, Timothy N. Sletten, and Sang M. Lee. ZEUS: A Knowledge-Based Expert System that Assists in Predicting Visibility at Airbases. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada184197.

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Tsidylo, Ivan M., Serhiy O. Semerikov, Tetiana I. Gargula, Hanna V. Solonetska, Yaroslav P. Zamora, and Andrey V. Pikilnyak. Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic. CEUR Workshop Proceedings, 2021. http://dx.doi.org/10.31812/123456789/4370.

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The article describes the stages of modeling an intelligent system for evaluating multilevel test tasks based on fuzzy logic in the MATLAB application package, namely the Fuzzy Logic Toolbox. The analysis of existing approaches to fuzzy assessment of test methods, their advantages and disadvantages is given. The considered methods for assessing students are presented in the general case by two methods: using fuzzy sets and corresponding membership functions; fuzzy estimation method and generalized fuzzy estimation method. In the present work, the Sugeno production model is used as the closest

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O'Neill, H. B., S. A. Wolfe, and C. Duchesne. Ground ice map of Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330294.

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This Open File presents national-scale mapping of ground ice conditions in Canada. The mapping depicts a first-order estimate of the combined volumetric percentage of excess ice in the top 5 m of permafrost from segregated, wedge, and relict ice. The estimates for the three ice types are based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019), and informed by available published values of ground ice content and expert knowledge. The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations bet

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Karam, Sofia, Morteza Nagahi, Vidanelage Dayarathna, Junfeng Ma, Raed Jaradat, and Michael Hamilton. Integrating systems thinking skills with multi-criteria decision-making technology to recruit employee candidates. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41026.

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The emergence of modern complex systems is often exacerbated by a proliferation of information and complication of technologies. Because current complex systems challenges can limit an organization's ability to efficiently handle socio-technical systems, it is essential to provide methods and techniques that count on individuals' systems skills. When selecting future employees, companies must constantly refresh their recruitment methods in order to find capable candidates with the required level of systemic skills who are better fit for their organization's requirements and objectives. The pur

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti

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Bourrier, Mathilde, Michael Deml, and Farnaz Mahdavian. Comparative report of the COVID-19 Pandemic Responses in Norway, Sweden, Germany, Switzerland and the United Kingdom. University of Stavanger, 2022. http://dx.doi.org/10.31265/usps.254.

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The purpose of this report is to compare the risk communication strategies and public health mitigation measures implemented by Germany, Norway, Sweden, Switzerland, and the United Kingdom (UK) in 2020 in response to the COVID-19 pandemic based on publicly available documents. The report compares the country responses both in relation to one another and to the recommendations and guidance of the World Health Organization where available. The comparative report is an output of Work Package 1 from the research project PAN-FIGHT (Fighting pandemics with enhanced risk communication: Messages, comp

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Minz, Dror, Stefan J. Green, Noa Sela, Yitzhak Hadar, Janet Jansson, and Steven Lindow. Soil and rhizosphere microbiome response to treated waste water irrigation. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7598153.bard.

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Research objectives : Identify genetic potential and community structure of soil and rhizosphere microbial community structure as affected by treated wastewater (TWW) irrigation. This objective was achieved through the examination soil and rhizosphere microbial communities of plants irrigated with fresh water (FW) and TWW. Genomic DNA extracted from soil and rhizosphere samples (Minz laboratory) was processed for DNA-based shotgun metagenome sequencing (Green laboratory). High-throughput bioinformatics was performed to compare both taxonomic and functional gene (and pathway) differences betwee

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GEOPLAY; a knowledge-based expert system; a model for exploration play analysis. US Geological Survey, 1995. http://dx.doi.org/10.3133/b2118.

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