Bibliografías temáticas / KEGG

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Literatura académica sobre el tema "KEGG"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 26 de julio de 2025

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Artículos de revistas sobre el tema "KEGG"

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Manyam, Ganiraju, Aybike Birerdinc, and Ancha Baranova. "KPP: KEGG Pathway Painter." BMC Systems Biology 9, Suppl 2 (2015): S3. http://dx.doi.org/10.1186/1752-0509-9-s2-s3.

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Sultana, Kazi Zakia, Anupam Bhattacharjee, and Hasan Jamil. "Querying KEGG pathways in logic." International Journal of Data Mining and Bioinformatics 9, no. 1 (2014): 1. http://dx.doi.org/10.1504/ijdmb.2014.057772.

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Kanehisa, M. "The KEGG databases at GenomeNet." Nucleic Acids Research 30, no. 1 (2002): 42–46. http://dx.doi.org/10.1093/nar/30.1.42.

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Kanehisa, Minoru, Miho Furumichi, Yoko Sato, Mari Ishiguro-Watanabe, and Mao Tanabe. "KEGG: integrating viruses and cellular organisms." Nucleic Acids Research 49, no. D1 (2020): D545—D551. http://dx.doi.org/10.1093/nar/gkaa970.

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Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which
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Hashimoto, Kosuke, Susumu Goto, Shin Kawano, et al. "KEGG as a glycome informatics resource." Glycobiology 16, no. 5 (2006): 63R—70R. http://dx.doi.org/10.1093/glycob/cwj010.

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Ogata, Hiroyuki, Susumu Goto, Wataru Fujibuchi, and Minoru Kanehisa. "Computation with the KEGG pathway database." Biosystems 47, no. 1-2 (1998): 119–28. http://dx.doi.org/10.1016/s0303-2647(98)00017-3.

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Slizen, Mikhail V., and Oxana V. Galzitskaya. "Comparative Analysis of Proteomes of a Number of Nosocomial Pathogens by KEGG Modules and KEGG Pathways." International Journal of Molecular Sciences 21, no. 21 (2020): 7839. http://dx.doi.org/10.3390/ijms21217839.

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Nosocomial (hospital-acquired) infections remain a serious challenge for health systems. The reason for this lies not only in the local imperfection of medical practices and protocols. The frequency of infection with antibiotic-resistant strains of bacteria is growing every year, both in developed and developing countries. In this work, a pangenome and comparative analysis of 201 genomes of Staphylococcus aureus, Enterobacter spp., Pseudomonas aeruginosa, and Mycoplasma spp. was performed on the basis of high-level functional annotations—KEGG pathways and KEGG modules. The first three organism
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Zhang, Chao, Zhongwei Chen, Miming Zhang, and Shulei Jia. "KEGG_Extractor: An Effective Extraction Tool for KEGG Orthologs." Genes 14, no. 2 (2023): 386. http://dx.doi.org/10.3390/genes14020386.

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The KEGG Orthology (KO) database is a widely used molecular function reference database which can be used to conduct functional annotation of most microorganisms. At present, there are many KEGG tools based on the KO entries for annotating functional orthologs. However, determining how to efficiently extract and sort the annotation results of KEGG still hinders the subsequent genome analysis. There is a lack of effective measures used to quickly extract and classify the gene sequences and species information of the KEGG annotations. Here, we present a supporting tool: KEGG_Extractor for specie
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Kanehisa, M. "The KEGG resource for deciphering the genome." Nucleic Acids Research 32, no. 90001 (2004): 277D—280. http://dx.doi.org/10.1093/nar/gkh063.

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Ogata, H., S. Goto, K. Sato, W. Fujibuchi, H. Bono, and M. Kanehisa. "KEGG: Kyoto Encyclopedia of Genes and Genomes." Nucleic Acids Research 27, no. 1 (1999): 29–34. http://dx.doi.org/10.1093/nar/27.1.29.

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Tesis sobre el tema "KEGG"

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Marabello, Anna Chiara <1962&gt. "CoMeta: studio delle distanze tra pathway metabolici di organismi in KEGG." Master's Degree Thesis, Università Ca' Foscari Venezia, 2013. http://hdl.handle.net/10579/2935.

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L'insieme di tutti i processi biochimici che avvengono in un organismo viene chiamato metabolismo. Il metabolismo è rappresentato da una rete metabolica suddivisa in vie metaboliche. Le vie metaboliche sono insiemi di reazioni che realizzano particolari funzioni biologiche. Esse trovano una naturale rappresentazione nelle reti di Petri. Entrambe infatti sono costituite da insiemi di reazioni che consumano e producono risorse. In questo lavoro, viene utilizzato il framework CoMeta che permette di confrontare vie metaboliche di organismi diversi rappresentate da reti di Petri. CoMeta utilizza di
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Rajasimha, Harsha Karur. "PathMeld: A Methodology for The Unification of Metabolic Pathway Databases." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/36325.

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A biological pathway database is a database that describes biochemical pathways, reactions, enzymes that catalyze the reactions, and the substrates that participate in these reactions. A pathway genome database (PGDB) integrates pathway information with information about the complete genome of various sequenced organisms. Two of the popular PGDBs available today are the Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaCyc. The proliferation of biological databases in general raises several questions for the life scientist. Which of these databases is most accurate, most current, or most
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Johnson, Stephen Robert. "iPathCase." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1327935542.

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守屋, 勇樹. "ゲノムからのパスウェイ推定の為のバイオインフォマティクス研究". 京都大学 (Kyoto University), 2017. http://hdl.handle.net/2433/225302.

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Aloraini, Adel Abdullah M. "Extending the graphical representation of four KEGG pathways for a better understanding of prostate cancer using machine learning of graphical models." Thesis, University of York, 2011. http://etheses.whiterose.ac.uk/1711/.

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This thesis shows a novel contribution to computational biology alongside with developed machine learning methods. It shows how the graphical representation of KEGG pathways can be refined using machine learning of graphical models. The focus mainly is on a set of graphical models called Bayesian networks. Throughout this thesis , different ways of learning Bayesian networks are discussed. The work is based on Affymetrix gene expression microarray profiles and penalised Gaussian linear models. Penalisation in linear models includes choosing the most important parents and estimating the associa
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Csombordi, Rajmund. "Metabolomics database resolver." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417525.

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Metabolomics is a rising field combining bioinformatics and cheminformatics together. A major component of research is having a reliable data source, which usually comes in the form of metabolomic databases. This paper documents arising issues revolving categorizing metabolome compounds within databases, and a possible solution in the form of an R package that is capable of matching up various metabolome identifiers that originate from various metabolome databases. Then, by using this package we reflect on the average coverage of external reference between metabolome databases to highlight the
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Ganesan, Sukirth M. "Relative Contributions Of Tobacco Associated Factors And Diabetes To Shaping The Oral Microbiome." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1529572658170786.

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Cheung, Ka-wing, and 張嘉穎. "Spatial and seasonal variations of freshwater macroinvertebrates, odonata and waterbirds in Luk Keng marshland, Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41290951.

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Isik, Zerrin, Tulin Ersahin, Volkan Atalay, Cevdet Aykanat, and Rengul Cetin-Atalay. "A signal transduction score flow algorithm for cyclic cellular pathway analysis, which combines transcriptome and ChIP-seq data." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-138982.

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Determination of cell signalling behaviour is crucial for understanding the physiological response to a specific stimulus or drug treatment. Current approaches for large-scale data analysis do not effectively incorporate critical topological information provided by the signalling network. We herein describe a novel model- and data-driven hybrid approach, or signal transduction score flow algorithm, which allows quantitative visualization of cyclic cell signalling pathways that lead to ultimate cell responses such as survival, migration or death. This score flow algorithm translates signalling
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Tam, Tat-kuen. "Geology of Tiu Keng Leng new development area." View the Table of Contents & Abstract, 2001. http://sunzi.lib.hku.hk/hkuto/record/B30109243.

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Libros sobre el tema "KEGG"

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Stephanie, Vaughan, and Temple Tory, eds. Kegs and dorms. Torquere Press, 2008.

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Poga, Laima. Kristaps Keggi: Intervijas. Jumava, 2000.

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Beng, Ooi Kee. Keng qiang Jixiang. Yi teng yan jiu zhong xin, 2012.

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Ximing, Chen, ed. Keng tou shi. Fujian mei shu chu ban she, 2002.

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Harte, Bryce. Powder keg. Berkley Books, 1991.

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Mingjin, Zheng, ed. Kuang dang keng dang. Xin yi ji jin chu ban she, 2003.

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Pirie, Robert W. The kirkyards of Keig. Aberdeen & North-East Scotland Family History Society, 2001.

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Qian, You. Xian tu you keng. Jiu zhou chu ban she, 2017.

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1964-, Tian Zi, ed. Keng qiang er ren xing. Zhongguo Hua qiao chu ban she, 2001.

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Sakura, Momoko. Hora abunai yo! Kega, yakedo. Kin no hoshisha, 1999.

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Capítulos de libros sobre el tema "KEGG"

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Mehlhorn, Heinz. "KEGG." In Encyclopedia of Parasitology. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-43978-4_4597.

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Mehlhorn, Heinz. "KEGG." In Encyclopedia of Parasitology. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-27769-6_4597-1.

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Kanehisa, Minoru. "KEGG GLYCAN." In A Practical Guide to Using Glycomics Databases. Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-56454-6_9.

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Qiu, Yu-Qing. "KEGG Pathway Database." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_472.

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Aoki-Kinoshita, Kiyoko F., and Minoru Kanehisa. "Glycomic Analysis Using KEGG GLYCAN." In Methods in Molecular Biology. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2343-4_7.

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Paul, Bini Elsa, Olaa Kasem, Haitao Zhao, and Zhong-Hui Duan. "Common Motifs in KEGG Cancer Pathways." In Advances in Computer Vision and Computational Biology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71051-4_60.

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Tokimatsu, Toshiaki, Masaaki Kotera, Susumu Goto, and Minoru Kanehisa. "KEGG and GenomeNet Resources for Predicting Protein Function from Omics Data Including KEGG PLANT Resource." In Protein Function Prediction for Omics Era. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0881-5_14.

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Aoki-Kinoshita, Kiyoko F., and Minoru Kanehisa. "Gene Annotation and Pathway Mapping in KEGG." In Comparative Genomics. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-515-2_6.

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Masoudi-Nejad, Ali, Susumu Goto, Takashi R. Endo, and Minoru Kanehisa. "KEGG Bioinformatics Resource for Plant Genomics Research." In Plant Bioinformatics. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-535-0_21.

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Kotera, Masaaki, Yuki Moriya, Toshiaki Tokimatsu, Minoru Kanehisa, and Susumu Goto. "KEGG and GenomeNet, New Developments, Metagenomic Analysis." In Encyclopedia of Metagenomics. Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7478-5_694.

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Actas de conferencias sobre el tema "KEGG"

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Gerasch, Andreas, Michael Kaufmann, and Oliver Kohlbacher. "Rebuilding KEGG Maps: Algorithms and Benefits." In 2014 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2014. http://dx.doi.org/10.1109/pacificvis.2014.45.

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KANEHISA, MINORU. "KEGG FOR MEDICAL AND PHARMACEUTICAL APPLICATIONS." In The 6th Asia-Pacific Bioinformatics Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2007. http://dx.doi.org/10.1142/9781848161092_0002.

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Judeh, Thair, Tin Chi Nguyen, and Dongxiao Zhu. "QSEAfor fuzzy subgraph querying of KEGG pathways." In the ACM Conference. ACM Press, 2012. http://dx.doi.org/10.1145/2382936.2382997.

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Muntyan, Victoria S., Mariia E. Vladimirova, Alexey M. Afonin, Alexey N. Muntyan, and Marina L. Roumiantseva. "ANALYSIS OF SALT-SENSITIVE AND SALT-TOLERANT SINORHIZOBIUM MELILOTI STRAINS USING DNA MICROARRAY, PHENOTYPE MICROARRAY AND GENOME MINING TECHNIQUES." In 23rd SGEM International Multidisciplinary Scientific GeoConference 2023. STEF92 Technology, 2023. http://dx.doi.org/10.5593/sgem2023/6.1/s25.15.

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Nodule bacteria increase the resistance of host plants to abiotic stress factors; however, the role of the genetic potential of rhizobia in the formation of productive salt-tolerant plant-microbial symbiosis remains underestimated. The aim of the study was to evaluate the pool of genes responsible for the salt tolerance of the alfalfa microsymbiont, Sinorhizobium meliloti, using the DNA microarray technique, phenotype microarray (PM), NGS and NNGS-technologies and genome mining (antismash 5.0). As a result of the analysis of the genomes of strains contrastingly different in salt tolerance, it
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Ligtenberg, Willem P. A., Dragan Bosnacki, and Peter A. J. Hilbers. "Mining Maximal Frequent Subgraphs in KEGG Reaction Networks." In 2009 20th International Workshop on Database and Expert Systems Application. IEEE, 2009. http://dx.doi.org/10.1109/dexa.2009.66.

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Seipel, Dietmar. "Drug Design for KEGG Pathways with Answer Set Programming." In The International Symposium on Grids and Clouds (ISGC) 2012. Sissa Medialab, 2012. http://dx.doi.org/10.22323/1.153.0003.

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Zhou, Tingting, Samuel K. F. Yung, Zhenghua Wang, and Yunping Zhu. "A New Recursive Approach for Reconstructing Metabolic Networks from KEGG." In 2009 Fourth International Conference on Frontier of Computer Science and Technology (FCST). IEEE, 2009. http://dx.doi.org/10.1109/fcst.2009.28.

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D, Subhashini, and Daniel Alex Anand. "Network Biology of KEGG Enriched Viral Comorbidities in Psoriasis Subjects." In 2021 Innovations in Power and Advanced Computing Technologies (i-PACT). IEEE, 2021. http://dx.doi.org/10.1109/i-pact52855.2021.9696642.

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Sultana, Kazi Zakia, Anupam Bhattacharjee, and Hasan Jamil. "IsoKEGG: A logic based system for querying biological pathways in KEGG." In 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2010. http://dx.doi.org/10.1109/bibm.2010.5706642.

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Popescu, M., Dong Xu, and E. Taylor. "GoFuzzKegg: Mapping Genes to KEGG Pathways Using an Ontological Fuzzy Rule System." In 2007 4th Symposium on Computational Intelligence in Bioinformatics and Computational Biology. IEEE, 2007. http://dx.doi.org/10.1109/cibcb.2007.4221236.

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Informes sobre el tema "KEGG"

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Akto, P., Z. Chen, and K. Hu. Evaluation of geothermal resource potential of hot sedimentary aquifers in the Horn River Basin, northeast British Columbia, Canada. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331225.

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This study assesses the geothermal potential of Hot Sedimentary Aquifers underlying the Horn River Basin (HRB) based on analyses of borehole temperatures, geological and production data, core porosity and permeability measurements, and geophysical well logs. The proposed criteria are applied to evaluate the geothermal potential of the Horn River Group (HRG) and sub-HRG formations. Favourable spots are identified and ranked by applying temperature, thickness, porosity, permeability and flow rate mapping. The results show that the HRG and its underlying strata have a good potential of geothermal
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