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Discover Agriculture 2025年第1期3卷 1-17页

作者： Prabha, Ratna Samota, Mahesh K. Verma, M. K. Gupta, Shailendra Rai, Anil Dubey, S. C. Singh, D. P. Division of Agricultural Bioinformatics ICA-Indian Agricultural Statistics Research Institute New Delhi India Agricultural Knowledge Management Unit (AKMU) ICAR-Indian Agricultural Research Institute New Delhi India Chhattisgarh Swami Vivekananda Technical University Bhilai India ICAR-CIPHET Abohar India Department of Systems Biology and Bioinformatics University of Rostock Rostock Germany Indian Council of Agricultural Research New Delhi India ICAR-Indian Institute of Vegetable Research Varanasi India

Microbes inhabiting rhizosphere and soils of close vicinity of plants play a pivotal role in plant growth promotion, enhance plant fitness, and improve soil fertility through the cycling of different nutrients like carbon, nitrogen, sulphur etc. The study of rhizosphere and soil-associated microbiome can enhance our knowledge about different genes (known and novel, both) and pathways associated with various metabolic activities of immense importance. Current agricultural system is heavily dependent on numerous synthetic chemicals like insecticides, fungicides, and herbicides. Regular application of such chemicals has raised the issues of environmental pollution and imposed severe risks on human beings. With extensive research, microbes are now established as the most important means of pesticide degradation. The current study focuses on the identification of different genes and pathways involved in the degradation and remediation of various xenobiotics and their components in the 105 different metagenome and metatranscriptome samples of rhizosphere or associated soil of seven different crops, i.e. wheat, oat, pea, soybean, sugarcane, kodo and common bean. For different kinds of xenobiotics components, biodegradation and associated metabolism were analyzed and numerous gene and enzymes associated with these processes were identified. Statistical and computational analyses revealed several significant pathways, including benzoate degradation, central meta-cleavage pathway, salicylate and gentisate catabolism, and phenylacetyl-CoA catabolic pathway. Identified genes/enzymes are important for degradation of various xenobiotic including constituents of different pesticides. To facilitate access to this information, the researchers developed XenMetaDB, a comprehensive online database cataloging all identified enzymes and pathways, accessible at http://***/xenmetadb/ . Identification of xenobiotics degradating enzymes, genes and their further utilization

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Metatranscriptome analysis to identify the influence of diet over metabolic proficiency of rumen in Mehsani buffalo

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Dairy Science and Management 2025年第1期2卷 1-17页

作者： Prabha, Ratna Kumari, Rajni Kumar, Sanjay Bhati, Jyotika Mishra, D. C. Rai, Anil Samota, Mahesh K. Singh, D. P. Division of Agricultural Bioinformatics ICAR - Indian Agricultural Statistics Research Institute New Delhi India Agricultural Knowledge Management Unit (AKMU) ICAR-Indian Agricultural Research Institute New Delhi India Division of Livestock and Fishery Management ICAR - Research Complex for Eastern Region Patna India Department of Animal Nutrition Bihar Veterinary College Bihar Animal Sciences University Patna India ICAR-CIPHET Punjab India ICAR-Indian Institute of Vegetable Research Varanasi India

The rumen microbiome is a complex system of numerous microbes that play crucial role in digesting feed and are of particular interest for the extraction of enzymes for application in industries such as food, biofuel, and others. Metatranscriptome profiling gives insight into the genes being actively transcribed, providing a functional understanding of the rumen. Current study focuses over the analysis of rumen metatranscriptome samples from Mehsani buffalo, belonging to different diet treatments including dry and green roughage with varying amount of concentrate. The study aimed to determine the key biological processes in the rumen and how diet changes affect them. Results showed that the most prevalent microbial community was Prevotella and metabolic activities dominated, with carbohydrate metabolism, fermentation, and methanogenesis among the most abundant functional features. It was identified that functional profile of the rumen samples are majorly influenced by diet. The green roughage diet groups reflect high metabolic activity and contain genes for carbohydrate metabolism, which were not present in the dry roughage diet groups. Attempts were also taken to identify variation in fermentation and methanogenesis processes among these diet variations. Further, the study found that the type of diet greatly impacted the functional profile and have significant influence on metabolic capacity of animals. A set of 64 pathways were identified as significant ones in corresponds to diet variations and out of which 20 belongs to metabolic processes and this was further supported by differential abundance analysis, LEfSe and Random Forest analysis also, highlighting the importance of metabolism in rumen functionality. Metabolic pathways were more abundant in green roughage diets groups compared to dry roughage ones, indicating that green roughage stimulates more metabolic activity compared to dry roughage. Impact of concentrate in the diet was also visible. The study found

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The inclusion of variability and uncertainty evaluations in WWTP design by means of stochastic dynamic modeling: The case of Eindhoven 85

The inclusion of variability and uncertainty evaluations in ...

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85th Annual Water Environment Federation Technical Exhibition and Conference, WEFTEC 2012

作者： Benedetti, Lorenzo Belia, Evangelina Cierkens, Katrijn Flameling, Tony De Baets, Bernard Nopens, Ingmar Weijers, Stefan 50023 Italy Primodal Inc. 145 Aberdeen QuébecQCG1R 2C9 Canada BIOMATH Model-Based Biosystem Analysis and Optimisation Department of Mathematical Modelling Statistics and Bioinformatics Ghent University Coupure links 653 Gent9000 Belgium KERMIT Research Unit Knowledge-based Systems Department of Mathematical Modelling Statistics and Bioinformatics Ghent University Coupure links 653 Gent9000 Belgium Waterschap De Dommel PO Box 10.001 DA Boxtel5280 Netherlands

ISBN: (纸本)9781510870437

This paper illustrates how a dynamic model can be used to evaluate a plant upgrade using post-upgrade performance data. The case study is that of the Eindhoven WWTP upgrade completed in 2006. As a first step, the design process was analyzed and the choices regarding variability and uncertainty (i.e. safety factors) were made explicit. As a second step, a dynamic model of the plant was set up, able to reproduce the anticipated variability. The third step was to define probability density functions for the parameters assumed to be uncertain, and propagate that uncertainty with the dynamic model by means of Monte Carlo simulations. The last step was the statistical evaluation of the simulation results. This work should be regarded as a "learning exercise" increasing the understanding of how and to what extent variability and uncertainty are currently incorporated in design guidelines and how model-based post-project appraisals could be performed. Copyright © 2012 Water Environment Federation. All Rights Reserved.

关键词： Design

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Influence of uncertainty analysis methods and subjective choices on prediction uncertainty for a respirometric case

Influence of uncertainty analysis methods and subjective cho...

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6th Biennial Meeting of the International Environmental Modelling and Software Society: Managing Resources of a Limited Planet, iEMSs 2012

作者： Cierkens, Katrijn Van Hoey, Stijn De Baets, Bernard Seuntjens, Piet Nopens, Ingmar Department of Mathematical Modelling Statistics and Bioinformatics BIOMATH Model-Based Biosystem Analysis and Optimisation Ghent University Coupure Links 653 B-9000 Ghent Belgium Department of Mathematical Modelling Statistics and Bioinformatics Research Unit Knowledge-Based Systems Ghent University Coupure links 653 B-9000 Ghent Belgium Boeretang 200 B-2400 Mol Belgium Department of Soil Management Ghent University Coupure Links 653 9000 Ghent Belgium Faculty of Bioscience Engineering University of Antwerp Groenenborgerlaan 171 2020 Antwerp Belgium

ISBN: (纸本)9788890357428

Uncertainty analysis in integrated wastewater treatment modelling is still in its infancy, although techniques from different fields are increasingly used in research for design and control of wastewater treatment plants (WWTPs). However, results should be interpreted with care. This paper shows explicitly the influence of different methodologies and subjective choices on prediction uncertainty for a simple environmental modelling case: A respirometric experiment for acetate degradation without storage. This case uses experimental data and can be used to estimate kinetic parameters of activated sludge in full-scale wastewater treatment modelling. These are subsequently used in more complex activated sludge models (ASMs) for dynamic modelling studies, in order to reduce the number of parameters to calibrate in these overparameterised models. Three uncertainty analysis methodologies are compared: (1) classical parameter estimation (Fisher Information Matrix or FIM-based), which has been performed extensively for respirometric models. The derived parameter confidence intervals are then propagated to the output through Monte Carlo (MC) simulations with and without correlation based sampling;(2) MC simulations from expert-based probability density functions;(3) the generalised likelihood uncertainty estimation (GLUE) method, a well-known uncertainty analysis method applied in hydrological modelling, recently also applied on full-scale WWTPs. The output uncertainty boundaries on the model output are very specific to the method used and to subjective choices like probability density functions in the expert-based method and threshold values in the GLUE method. Besides, classical parameter estimation and GLUE are useful to observe and easily handle correlated parameters, which is very important when using these methods on full-scale models. Appropriate validation experiments are needed to judge the applicability of the different applied methods. Whereas this seems not possib

关键词： Uncertainty analysis

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Advancing translational research with the Semantic Web

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BMC bioinformatics 2007年第SUPPL. 3期8卷 1-16页

作者： Ruttenberg, Alan Clark, Tim Bug, William Samwald, Matthias Bodenreider, Olivier Chen, Helen Doherty, Donald Forsberg, Kerstin Gao, Yong Kashyap, Vipul Kinoshita, June Luciano, Joanne Marshall, Scott M. Ogbuji, Chimezie Rees, Jonathan Stephens, Susie Wong, Gwendolyn T. Wu, Elizabeth Zaccagnini, Davide Hongsermeier, Tonya Neumann, Eric Herman, Ivan Cheung, Kei-Hoi Millennium Pharmaceuticals Cambridge MA United States Initiative in Innovative Computing Harvard University Cambridge MA United States Laboratory for Bioimaging and Anatomical Informatics Department of Neurobiology and Anatomy Drexel University College of Medicine Philadelphia PA United States Section on Medical Expert and Knowledge-Based Systems Medical University of Vienna Vienna Austria National Library of Medicine Bethesda MD United States Agfa Healthcare Waterloo ON Canada Brainstage Research Pittsburgh PA United States AstraZeneca Mölndal Sweden MassGeneral Institute for Neurodegenerative Disease Massachusetts General Hospital Charlestown MA United States Partners HealthCare System Wellesley MA United States Alzheimer Research Forum Boston MA United States Harvard Medical School Boston MA United States Integrative Bioinformatics Unit University of Amsterdam Amsterdam Netherlands Cleveland Clinic Foundation Cleveland OH United States Science Commons Cambridge MA United States Oracle Burlington MA United States Language and Computing Reston VA United States Teranode Corporation Seattle WA United States New Haven CT United States Center for Medical Informatics Yale University School of Medicine New Haven CT United States

Background: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. Results: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Conclusion: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of p

关键词： Clinical research

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Interactions between trabecular meshwork cells and lens epithelial cells – a possible mechanism in infantile aphakic glaucoma

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Acta Ophthalmologica 2008年第S243期86卷

作者： M INBAL M SHMOISH DS WALTON S LEVENBERG Technion- Israel Institute of Technology Faculty of Bio-Medical Engineering Haifa Technion- Israel Institute of Technology Bioinformatics Knowledge Unit The Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering Haifa Glaucoma Service Massachusetts Eye and Ear Infirmary and Harvard Medical School Boston

Purpose Infantile aphakic glaucoma may develop as a postoperative complication of early childhood cataract surgery. Its causes and mechanisms to date are poorly understood. Our goal is to study the mechanisms leading to trabecular meshwork (TM) dysfunction and glaucoma following the cataract removal. We focus on deciphering the interactions between TM cells and lens tissue or conditioned medium by analyzing changes in TM cells co-cultured with lens epithelial cells (LECs), or cultured in the presence of factors found to be secreted by LECs. Methods These interactions are studied by analyzing for morphological alternations, and differential gene and protein expression. Factors secreted by LECs are analyzed using cytokines array membranes. Results TM cells grown in the presence of LECs exhibited structural changes (mainly volume and size enlargement and decreased cell-cell interactions), as well as altered protein expression (mainly cytoskeletal), and gene expression (such as genes related to cell morphogenesis and inflammatory response). Several cytokines were found to be elevated in the medium of LECs, and of the co-culture, but not in the medium of TM cells, suggesting their role in the changes observed in TM cells co cultured with LECs; co-culture of TM cells in the presence of these cytokines will be further performed. Conclusion Many of these changes were reported in primary open-angle glaucoma, suggesting the possible role of LECs in the development of aphakic glaucoma.

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Publisher Correction: Increasing the presence of BIPOC researchers in computational science

Nature computational science

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Nature computational science 2024年第10期4卷 798页

作者： Christine Yifeng Chen Alan Christoffels Roger Dube Kamuela Enos Juan E Gilbert Sanmi Koyejo Jason Leigh Carlo Liquido Amy McKee Kari Noe Tai-Quan Peng Karaitiana Taiuru Cosmochemical and Isotopic Signatures Group Nuclear and Chemical Sciences Division Lawrence Livermore National Laboratory Livermore CA USA. chen127@llnl.gov. South African MRC (SAMRC) Bioinformatics Unit South African National Bioinformatics Institute University of the Western Cape Cape Town South Africa. alan@sanbi.ac.za. Africa Centers for Disease Control and Prevention African Union Addis Ababa Ethiopia. alan@sanbi.ac.za. College of Science Rochester Institute of Technology Rochester NY USA. rrdube@***. Office of Indigenous Knowledge and Innovation University of Hawai'i Honolulu HI USA. kenos@hawaii.edu. Computer & Information Science & Engineering Department University of Florida Gainesville FL USA. juan@ufl.edu. Department of Computer Science Stanford University Stanford CA USA. sanmi@cs.stanford.edu. Department of Information and Computer Sciences University of Hawai'i at Mānoa Honolulu HI USA. leighj@hawaii.edu. Pi'ikū Co. Kailua HI USA. carlo.h.liquido@***. Department of Educational Foundations University of Hawai'i at Mānoa Honolulu HI USA. amymckee@hawaii.edu. 'ĀinaQuest Honolulu HI USA. amymckee@hawaii.edu. Office of Indigenous Knowledge and Innovation University of Hawai'i Honolulu HI USA. karinoe@hawaii.edu. Department of Communication Michigan State University East Lansing MI USA. pengtaiq@msu.edu. Taiuru & Associates Limited Auckland New Zealand. karaitiana@taiuru.maori.nz. Ngāi Tahu Ngāti Kahungunu Ngāti Toa Auckland New Zealand. karaitiana@taiuru.maori.nz.

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Cover Picture: ConSurf: Using Evolutionary Data to Raise Testable Hypotheses about Protein Function / JSmol and the Next-Generation Web-Based Representation of 3D Molecular Structure as Applied toProteopedia(Isr. J. Chem. 3-4/2013)

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Israel Journal of Chemistry 2013年第3‐4期53卷

作者： Gershon Celniker Guy Nimrod Haim Ashkenazy Fabian Glaser Eric Martz Itay Mayrose Tal Pupko Nir Ben-Tal Robert M. Hanson Jaime Prilusky Zhou Renjian Takanori Nakane Joel L. Sussman The Department of Biochemistry and Molecular Biology Tel Aviv University 69978 Tel Aviv (Israel) The Department of Cell Research and Immunology Tel Aviv University 69978 Tel Aviv (Israel) The Department of Molecular Biology and Ecology of Plants Tel Aviv University 69978 Tel Aviv (Israel) Present address: Biolojic Design Akiva Aria 25 Tel Aviv 6215425 (Israel) Bioinformatics Knowledge Unit The Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering Technion – Israel Institute of Technology Haifa 32000 (Israel) Department of Microbiology University of Massachusetts Amherst MA (USA) Joel L. Sussman Dept. of Structural Biology and the Israel Structural Proteomics Center Weizmann Institute of Science Rehovot 76100 (Israel) phone +972-8-934-4531 fax: +972-8-934-6312 St. Olaf College Dept. of Chemistry Northfield MN 55057 (USA) R. M. H. and J. P. made equal contribution to this paper. Bioinformatics Unit Biological Services Weizmann Institute of Science Rehovot 76100 (Israel) Room 202 Building 38 Nianjiabang Road 425 Zhoupu Town Pudong District Shanghai 201318 (China) Dept. of Cell Biology Graduate School of Medicine Kyoto University Yoshidakonoe-cho Sakyo-ku Kyoto 606-8501 (Japan) Dept. of Structural Biology and the Israel Structural Proteomics Center Weizmann Institute of Science Rehovot 76100 (Israel) phone +972-8-934-4531 fax: +972-8-934-6312 Nir Ben-Tal The Department of Biochemistry and Molecular Biology Tel Aviv University 69978 Tel Aviv (Israel)

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Correction to: Transcriptome-wide identification of genes involved in Ascorbate-Glutathione cycle (Halliwell-Asada pathway) and related pathway for elucidating its role in antioxidative potential in finger millet ( Eleusine coracana (L.))

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3 Biotech 2019年第9期9卷 337页

作者： Himanshu Avashthi Rajesh Kumar Pathak Neetesh Pandey Sandeep Arora Amrendra Kumar Mishra Vijai Kumar Gupta Pramod Wasudeo Ramteke Anil Kumar Department of Computational Biology and Bioinformatics Sam Higginbottom University of Agriculture Technology and Sciences Allahabad Uttar Pradesh India. 2Agricultural Knowledge Management Unit ICAR-Indian Agricultural Research Institute Pusa New Delhi India. Department of Biotechnology Govind Ballabh Pant Institute of Engineering and Technology Pauri Garhwal Uttarakhand India. 4Present Address: School of Agricultural Biotechnology Punjab Agricultural University Ludhiana Punjab India. 5Department of Computational Biology Indraprastha Institute of Information Technology Delhi New Delhi India. 6Department of Molecular Biology and Genetic Engineering G. B. Pant University of Agriculture and Technology Pantnagar Uttarakhand India. 7Department of Chemistry and Biotechnology Tallinn University of Technology Tallinn Estonia. Department of Biological Sciences Sam Higginbottom University of Agriculture Technology and Sciences Allahabad Uttar Pradesh India. Present Address: Rani Lakshmi Bai Central Agricultural University Jhansi Uttar Pradesh India.

[This corrects the article DOI: 10.1007/s13205-018-1511-9.].

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Publisher Correction: Synthesis of Saccharumoside-B analogue with potential of antiproliferative and pro-apoptotic activities

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Scientific reports 2020年第1期10卷 185页

作者： Srinuvasarao Rayavarapu Nagendra Sastry Yarla Sunanda Kumari Kadiri Anupam Bishayee Siddaiah Vidavalur Ramu Tadikonda Mahaboob Basha Vijaya Rao Pidugu Kaladhar S V G K Dowluru Dhananjaya Bhadrapura Lakappa Mohammad A Kamal Ghulam Md Ashraf Vadim V Tarasov Vladimir N Chubarev Sergey G Klochkov George E Barreto Sergey O Bachurin Gjumrakch Aliev Department of Organic Chemistry Foods Drugs and Water College of Science and Technology Andhra University Visakhapatnam 530 003 Andhra Pradesh India. Department of Biochemistry and Bioinformatics School of Life Sciences Institute of Science GITAM University Visakhapatnam 530 045 Andhra Pradesh India. Department of Animal Biology University of Hyderabad Hyderabad 500 046 Telangana India. Department of Microbiology College of Science and Technology Andhra University Visakhapatnam 530 003 Andhra Pradesh India. Department of Pharmaceutical Sciences College of Pharmacy Larkin Health Sciences Institute Miami FL 33169 USA. Excelra Knowledge Solutions Private Limited NSL SEZ ARENA IDA Uppal Hyderabad 500 039 Telangana India. Department of Microbiology and Bioinformatics Bilaspur University Bilaspur 495 001 Chhattisgarh India. Toxinology/Toxicology and Drug Discovery Unit Center for Emerging Technologies Jain Global Campus Jain University Kanakapura Taluk Ramanagara 562 112 Karnataka India. Enzymoics and Novel Global Community Educational Foundation Hebersham NSW Australia. King Fahd Medical Research Center King Abdulaziz University Jeddah Saudi Arabia. Institute of Pharmacy and Translational Medicine Sechenov First Moscow State Medical University 119991 Moscow Russia. Institute of Physiologically Active Compounds of the Russian Academy of Sciences Severniy Proezd Chernogolovka Moscow Region 1142432 Russia. Departamento de Nutrición y Bioquímica Facultad de Ciencias Pontificia Universidad Javeriana Bogotá D. C. Colombia. Instituto de Ciencias Biomédicas Universidad Autónoma de Chile Santiago Chile. Institute of Physiologically Active Compounds of the Russian Academy of Sciences Severniy Proezd Chernogolovka Moscow Region 1142432 Russia. aliev03@***. "GALLY" International Biomedical Research Consulting LLC San Antonio TX 78229 USA. aliev03@***. School of Health Sciences and Healthcare Administration University of Atlanta Johns Creek GA 3

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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