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2nd International Conference on Data Engineering and Communication Technology, ICDECT 2017

作者： Choudhury, Ananya Subramanian, Rajamenakshi R. Sunder, Gaur High Performance Computing—Medical and Bioinformatics Application Group Centre for Development of Advanced Computing Pune India

ISBN: (纸本)9789811316098

Treatment in oncology relies heavily on imaging. Automatic identification of cancerous tumors is a challenging and time-taking task. This paper presents a multi-objective genetic algorithm for calculating optimal threshold value for binarization of CT lung images and segmentation of the tumor region using connected component analysis. The threshold determination method is tested on two public datasets: Data Science Bowl: Stage 1 and NSCLC lung cancer dataset. The results obtained are compared with other genetic algorithm approach and traditional Otsu’s method. The proposed method gives better threshold value compared to Otsu’s method and outperforms other genetic algorithm approach both in terms of threshold value and computation time. Connected component analysis is done on the labeled connected component in the binarized image. Based on predetermined geometric measurements, the components are marked as tumors and non-tumors. This method when applied to 240 cancerous images, correctly identified tumors for 205 images while showed no result where there are no tumors in the image. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Tumors

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Landscape of global urban environmental resistome and its association with local socioeconomic and medical status

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Science China(Life Sciences) 2024年第6期67卷 1292-1301页

作者： Jun Wu Yige Hu Michael H Perlin David Danko Jun Lu Manuela Oliveira Johannes Werner Maria M Zambrano Maria A Sierra Olayinka O Osuolale Paweł Łabaj Nicolás Rascovan Nur Hazlin Hazrin-Chong Soojin Jang Haruo Suzuki Marina Nieto-Caballero Bharath Prithiviraj Patrick K H Lee Agnieszka Chmielarczyk Anna Różańska Yongxiang Zhao Lan Wang Christopher E Mason Tieliu Shi Center for Bioinformatics and Computational Biology and the Institute of Biomedical SciencesSchool of Life SciencesEast China Normal UniversityShanghai 200241China Department of Biology Program on Disease EvolutionUniversity of LouisvilleLouisville 40292USA Weill Cornell Medicine New York 10065USA The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine New York 10065USA Department of Pulmonary Medicine Shanghai Chest HospitalShanghai Jiao Tong UniversityShanghai 200025China i3S-Instituto de Investiga玢o e Inova玢o em Saúde Universidade do PortoPorto 4050-290Portugal Ipatimup-Instituto de Patologia e Imunologia Molecular da Universidade do Porto Porto 4200-465Portugal Departamento de Biologia Faculdade de CiênciasUniversidade do PortoPorto 4050-290Portugal High Performance and Cloud Computing Group Zentrum für Datenverarbeitung(ZDV)Eberhard Karls University of TübingenW鋍hterstra遝7672074TübingenGermany Corporación Corpogen Research Center Bogotá110311Colombia Applied Environmental Metagenomics and Infectious Diseases Research(AEMIDR) Department of Biological SciencesElizade UniversityIlara-Mokin 340271Nigeria Maopolska Centre of Biotechnology Jagiellonian UniversityKraków 30-005Poland Aix-Marseille Université Mediterranean Institute of OceanologyUniversitéde ToulonCNRSIRDUM 110Marseille 83041France Department of Biological Sciences and Biotechnology Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangor Institut Pasteur Korea Seoul 13488Republic of Korea Faculty of Environment and Information Studies Keio UniversityFujisawaKanagawa 252-0882Japan University of Colorado at Boulder CivilEnvironmental and Architectural DepartmentBoulder 80303USA Brooklyn College of the City University of New York Brooklyn 11210USA School of Energy and Environment City University of Hong KongHong Kong 999077China Department of Microbiology Faculty of MedicineJagiellonian UniversityKraków 30-005Poland Biological Targeting Diagnosis and The

Antimicrobial resistance(AMR)poses a critical threat to global health and development,with environmental factors—particularly in urban areas—contributing significantly to the spread of antibiotic resistance genes(ARGs).However,most research to date has been conducted at a local level,leaving significant gaps in our understanding of the global status of antibiotic resistance in urban *** address this issue,we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples,which were collected by the Meta SUB International Consortium involving diverse urban environments in 60 cities of 27 countries,utilizing a deep-learning based *** findings demonstrated the strong geographical specificity of urban environmental resistome,and their correlation with various local socioeconomic and medical *** also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters(BGCs)across different countries,and discovered that the urban environment represents a rich source of novel *** study provides a comprehensive overview of the global urban environmental resistome,and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.

关键词： urban environment metagenome antibiotic resistance resistance diversity biosynthetic gene clusters

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Raptor: A Five-Safes Approach to a Secure, Cloud Native and Serverless Genomics Data Repository

SSRN

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SSRN 2022年

作者： Shih, Chih Chuan Chen, Jieqi Lee, Ai Shan Bertin, Nicolas Hebrard, Maxime Khor, Chiea Chuen Li, Zheng Tan, Joanna Hui Juan Meah, Wee Yang Peh, Su Qin Mok, Shi Qi Sim, Kar Seng Liu, Jianjun Wang, Ling Wong, Eleanor Li, Jingmei Tin, Aung Cheng, Ching-Yu Heng, Chew-Kiat Yuan, Jian-Min Koh, Woon-Puay Saw, Seang Mei Friedlander, Yechiel Sim, Xueling Chai, Jin Fang Chong, Yap Seng Davila, Sonia Goh, Liuh Ling Lee, Eng Sing Wong, Tien Yin Karnani, Neerja Leong, Khai Pang Yeo, Khung Keong Chambers, John C. Lim, Su Chi Goh, Rick Siow Mong Tan, Patrick Dorajoo, Rajkumar Genome Institute of Singapore Agency for Science Technology and Research Singapore Singapore Eye Research institute Singapore National Eye Centre Singapore Yong Loo Lin School of Medicine National University of Singapore Singapore Duke-NUS Medical School Singapore Singapore National Eye Centre Singapore Department of Paediatrics Yong Loo Lin School of Medicine National University of Singapore Singapore Khoo Teck Puat - National University Children's Medical Institute National University Health System Singapore Department of Epidemiology Graduate School of Public Health University of Pittsburgh PittsburghPA United States UPMC Hillman Cancer Center University of Pittsburgh PittsburghPA United States Healthy Longevity Translational Research Programme Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Institute for Clinical Sciences Agency for Science Technology and Research Singapore Saw Swee Hock School of Public Health National University of Singapore Singapore Braun School of Public Health Hebrew University of Jerusalem Jerusalem Israel Precision Health Research Singapore SingHealth Duke-NUS Institute of Precision Medicine Singapore Molecular Diagnostic Laboratory Tan Tock Seng Hospital Singapore Clinical Research Unit National Healthcare Group Polyclinics Singapore Lee Kong Chian School of Medicine Nanyang Technological University Singapore Bioinformatics Institute Agency for Science Technology and Research Singapore Personalised Medicine Service Tan Tock Seng Hospital Singapore Department of Cardiology National Heart Centre Singapore Singapore School of Public Health Imperial College London United Kingdom Clinical Research Unit Khoo Teck Puat Hospital Singapore Diabetes Centre Admiralty Medical Centre Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore Cancer Science Institute of Singapore National University of Singapore Singapore

Genomic researchers are increasingly utilizing commercial cloud platforms (CCPs) to manage their data and analytics needs. Commercial clouds allow researchers to grow their storage and analytics capacity on demand, keeping pace with expanding project data footprints and enabling researchers to avoid large capital expenditures while paying only for IT capacity consumed by their project. Cloud computing also allows researchers to overcome common network and storage bottlenecks encountered when combining or re-analysing large datasets. However, cloud computing presents a new set of challenges. Without adequate security controls, the risk of unauthorised access may be higher for data stored on the cloud. In addition, regulators are increasingly mandating data access patterns and specific security protocols on the storage and use of genomic data to safeguard rights of the study participants. While CCPs provide tools for security and regulatory compliance, utilising these tools to build the necessary controls required for cloud solutions is not trivial as such skill sets are not commonly found in a genomics lab. The Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud native genomics data repository and analytics platform focusing on security and regulatory compliance. Using a "five-safes" framework (Safe Purpose, Safe People, Safe Settings, Safe Data and Safe Output), RAPTOR provides security and governance controls to data contributors and users leveraging cloud computing for sharing and analysis of large genomic datasets without the risk of security breaches or running afoul of regulations. RAPTOR can also enable data federation with other genomic data repositories using GA4GH community-defined standards, allowing researchers to boost the statistical power of their work and overcome geographic and ancestry limitations of data sets © 2022, The Authors. All rights reserved.

关键词： Genome

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Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence

arXiv

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arXiv 2025年

作者： Sun, Yingying Jun, A. Liu, Zhiwei Sun, Rui Qian, Liujia Payne, Samuel H. Bittremieux, Wout Ralser, Markus Li, Chen Chen, Yi Dong, Zhen Perez-Riverol, Yasset Khan, Asif Sander, Chris Aebersold, Ruedi Vizcaíno, Juan Antonio Krieger, Jonathan R. Yao, Jianhua Wen, Han Zhang, Linfeng Zhu, Yunping Xuan, Yue Sun, Benjamin Boyang Qiao, Liang Hermjakob, Henning Tang, Haixu Gao, Huanhuan Deng, Yamin Zhong, Qing Chang, Cheng Bandeira, Nuno Li, Ming Weinan, E. Sun, Siqi Yang, Yuedong Omenn, Gilbert S. Zhang, Yue Xu, Ping Fu, Yan Liu, Xiaowen Overall, Christopher M. Wang, Yu Deutsch, Eric W. Chen, Luonan Cox, Jürgen Demichev, Vadim He, Fuchu Huang, Jiaxing Jin, Huilin Liu, Chao Li, Nan Luan, Zhongzhi Song, Jiangning Yu, Kaicheng Wan, Wanggen Wang, Tai Zhang, Kang Zhang, Le Bell, Peter A. Mann, Matthias Zhang, Bing Guo, Tiannan Affiliated Hangzhou First People’s Hospital State Key Laboratory of Medical Proteomics School of Medicine Westlake University Zhejiang Province Hangzhou China Westlake Center for Intelligent Proteomics Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Province Hangzhou China Biology Department Brigham Young University ProvoUT84602 United States Department of Computer Science University of Antwerp Antwerp2020 Belgium Department of Biochemistry CharitéUniversitätsmedizin Berlin Berlin Germany Biomedicine Discovery Institute Department of Biochemistry and Molecular Biology Monash University MelbourneVICVIC 3800 Australia Wellcome Genome Campus Hinxton CambridgeCB10 1SD United Kingdom Harvard Medical School Ludwig Center at Harvard United States Harvard Medical School Broad Institute Ludwig Center at Harvard Dana-Farber Cancer Institute United States Department of Biology Institute of Molecular Systems Biology ETH Zürich Zürich Switzerland Bruker Ltd. MiltonONL9T 6P4 Canada AI for Life Sciences Lab Tencent Shenzhen518057 China State Key Laboratory of Medical Proteomics AI for Science Institute Beijing100080 China Beijing Institute of Lifeomics Beijing102206 China Thermo Fisher Scientific GmbH Hanna-Kunath Str. 11 Bremen28199 Germany Informatics and Predictive Sciences Research Bristol Myers Squibb United States Department of Chemistry Fudan University Songhu Road 2005 Shanghai200438 China Department of Computer Science Luddy School of Informatics Computing and Engineering Indiana University IN47408 United States ProCan® Children’s Medical Research Institute Faculty of Medicine and Health The University of Sydney WestmeadNSW Australia La Jolla CA United States Central China Institute of Artificial Intelligence University of Waterloo Canada AI for Science Institute Center for Machine Learning Research School of Mathematical Sciences Peking University China Research Institute of Intelligent Complex Systems Fudan U

Artificial intelligence (AI) is transforming scientific research, including proteomics. Advances in mass spectrometry (MS)-based proteomics data quality, diversity, and scale, combined with groundbreaking AI techniques, are unlocking new challenges and opportunities in biological discovery. Here, we highlight key areas where AI is driving innovation, from data analysis to new biological insights. These include developing an AI-friendly ecosystem for proteomics data generation, sharing, and analysis;improving peptide and protein identification and quantification;characterizing protein-protein interactions and protein complexes;advancing spatial and perturbation proteomics;integrating multi-omics data;and ultimately enabling AI-empowered virtual cells. © 2025, CC BY.

关键词： Biotic

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Corrigendum to "Monastrol suppresses invasion and metastasis in human colorectal cancer cells by targeting fascin independent of kinesin-Eg5 pathway" [Biomed. Pharmacother. 175 (2024) 116785]

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Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2024年 179卷 117411页

作者： Begoña Alburquerque-González Silvia Montoro-García Ángel Bernabé-García Manuel Bernabé-García Priscila Campioni-Rodrigues Alejandro Rodríguez-Martínez Irene Luque Tuula Salo Alfonso Pérez-Garrido Horacio Pérez-Sánchez María Luisa Cayuela Ginés Luengo-Gil Enrico Luchinat Fatima Postigo-Corrales Tommaso Staderini Francisco José Nicolás Pablo Conesa-Zamora Health Sciences Faculty Universidad Católica de Murcia (UCAM) Guadalupe Spain. Regeneración Oncología Molecular y TGF-ß. IMIB-Arrixaca Carretera Madrid-Cartagena El Palmar 30120 Spain. Research group "Telomerasa Envejecimiento y Cáncer" CIBERER Hospital Clínico Universitario Virgen de la Arrixaca IMIB-Arrixaca Murcia Spain. ECM and Hypoxia research unit Faculty of Biochemistry and Molecular Medicine University of Oulu Aapistie 7C Oulu FI-90014 Finland Microelectronic Research Unit Faculty of Information Technology and Electrical Engineering University of Oulu Oulu FI-90570 Finland. Department of Physical Chemistry Institute of Biotechnology and Excellence Unit in Chemistry Applied to Biomedicine and Environment School of Sciences University of Granada Granada 18071 Spain Structural Bioinformatics and High-Performance Computing (BIO-HPC) Research Group Universidad Católica de Murcia (UCAM) Guadalupe Spain. Department of Physical Chemistry Institute of Biotechnology and Excellence Unit in Chemistry Applied to Biomedicine and Environment School of Sciences University of Granada Granada 18071 Spain. Oral Medicine and Pathology Research Unit of Population Health University of Oulu Finland Medical Research Center and Oulu University Hospital Aapistie 3 Oulu FI-90220 Finland Department of Oral and Maxillofacial Diseases University of Helsinki Haartmaninkatu 8 Helsinki FI-0014 Finland Translational Immunology Research Program (TRIMM) and iCAN Digital Precision Cancer Medicine Flagship University of Helsinki Finland Department of Pathology Helsinki University Hospital Helsinki Finland. Health Sciences Faculty Universidad Católica de Murcia (UCAM) Guadalupe Spain Pathology and Clinical Analysis Department Group of Molecular Pathology and Pharmacogenetics Instituto Murciano de Investigación Biosanitaria (IMIB) Hospital Universitario Santa Lucía Cartagena Spain. CERM - Magnetic Resonance Center and Dipartimento di Chimica Università degli Studi di Firenze Via Luigi

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