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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts

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The Lancet Respiratory Medicine 2020年第7期8卷 696-708页

作者： Moll, Matthew Sakornsakolpat, Phuwanat Shrine, Nick Hobbs, Brian D DeMeo, Dawn L John, Catherine Guyatt, Anna L McGeachie, Michael J Gharib, Sina A Obeidat, Ma'en Lahousse, Lies Wijnant, Sara R A Brusselle, Guy Meyers, Deborah A Bleecker, Eugene R Li, Xingnan Tal-Singer, Ruth Manichaikul, Ani Rich, Stephen S Won, Sungho Kim, Woo Jin Do, Ah Ra Washko, George R Barr, R Graham Psaty, Bruce M Bartz, Traci M Hansel, Nadia N Barnes, Kathleen Hokanson, John E Crapo, James D Lynch, David Bakke, Per Gulsvik, Amund Hall, Ian P Wain, Louise Soler Artigas, María Jackson, Victoria E Strachan, David P Hui, Jennie James, Alan L Kerr, Shona M Polasek, Ozren Vitart, Veronique Marten, Jonathan Rudan, Igor Kähönen, Mika Surakka, Ida Gieger, Christian Karrasch, Stefan Rawal, Rajesh Schulz, Holger Deary, Ian J Harris, Sarah E Enroth, Stefan Gyllensten, Ulf Imboden, Medea Probst-Hensch, Nicole M Lehtimäki, Terho Raitakari, Olli T Langenberg, Claudia Luan, Jian'an Wareham, Nick Zhao, Jing Hua Hayward, Caroline Murray, Alison Porteous, David J Smith, Blair H Jarvelin, Marjo-Riitta Wielscher, Matthias Joshi, Peter K Kentistou, Katherine A Timmers, Paul RHJ Wilson, James F Cook, James P Lind, Lars Mahajan, Anubha Morris, Andrew P Ewert, Ralf Homuth, Georg Stubbe, Beate Weiss, Stefan Zeggini, Eleftheria Weiss, Scott T Silverman, Edwin K Dudbridge, Frank Tobin, Martin D Cho, Michael H Channing Division of Network Medicine Brigham and Women's Hospital Boston MA United States Division of Pulmonary and Critical Care Medicine Brigham and Women's Hospital Boston MA United States Department of Medicine Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Genetic Epidemiology Group Department of Health Sciences University of Leicester Leicester United Kingdom Computational Medicine Core Center for Lung Biology Department of Medicine University of Washington Seattle WA United States Division of Pulmonary Critical Care and Sleep Medicine Department of Medicine University of Washington Seattle WA United States Cardiovascular Health Research Unit Department of Medicine University of Washington Seattle WA United States University of British Columbia Center for Heart Lung Innovation St Paul's Hospital Vancouver BC Canada Department of Epidemiology Erasmus Medical Centre Rotterdam Netherlands Department of Respiratory Medicine Erasmus Medical Centre Rotterdam Netherlands Department of Bioanalysis Faculty of Pharmaceutical Sciences Ghent University Ghent Belgium Department of Respiratory Medicine Ghent University Hospital Ghent Belgium Department of Medicine University of Arizona Tucson AZ United States GlaxoSmithKline Research and Development Collegeville PA United States Center for Public Health Genomics University of Virginia Charlottesville VA United States Department of Public Health Sciences University of Virginia Charlottesville VA United States Department of Public Health Sciences Graduate School of Public Health Seoul National University Seoul South Korea Interdisciplinary Program of Bioinformatics College of National Sciences Seoul National University Seoul South Korea Institute of Health and Environment Seoul National University Seoul South Korea Department of Internal Medicine Kangwon National University Chuncheon South Korea Department of Medicine and Department of Epidemiology Columbia Universit

Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. Methods: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV₁ and FEV₁/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV₁/FVC <0·7 and FEV₁ <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth. Findings: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74–1·88] and non-European (1·42 [1·34–1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56–9·72) in European ancestry and 4·83 (3·45–6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79–0·81] vs 0·76 [0·75–0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The po

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Corrigendum to "Dual regulatory effects of neferine on amyloid-β and tau aggregation studied by in silico, in vitro, and lab-on-a-chip technology" [Biomed. Pharmacother. 172 (2024) 1-14/116226]

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Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2024年 181卷 117686页

作者： Yunkwon Nam Ritu Prajapati Sujin Kim Soo Jung Shin Da Yeon Cheong Yong Ho Park Hyun Ha Park Danyou Lim Yoojeong Yoon Gyudo Lee Hyun Ah Jung Insu Park Dong-Hyun Kim Jae Sue Choi Minho Moon Department of Biochemistry College of Medicine Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea. Department of Food and Life Science Pukyong National University Busan 48513 Republic of Korea. Department of Biochemistry College of Medicine Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea Research Institute for Dementia Science Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea. Department of Biotechnology and Bioinformatics Korea University Sejong 30019 Republic of Korea Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong 30019 Republic of Korea. Department of Biomedical Engineering Konyang University Daejeon 35365 Republic of Korea. Department of Food Science and Human Nutrition Chonbuk National University Jeonju 54896 Republic of Korea. Department of Biomedical Engineering Konyang University Daejeon 35365 Republic of Korea. Electronic address: insupark@konyang.ac.kr. Departments of Pharmacology and Advanced Translational Medicine School of Medicine Konkuk University Seoul 05029 Republic of Korea. Electronic address: mose79@kku.ac.kr. Department of Food and Life Science Pukyong National University Busan 48513 Republic of Korea. Electronic address: choijs@pknu.ac.kr. Research Institute for Dementia Science Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea. Electronic address: hominmoon@konyang.ac.kr.

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Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation (vol 21, pg 432, 2018)

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NATURE NEUROSCIENCE 2018年第7期21卷 1015-1015页

作者： Preissl, Sebastian Fang, Rongxin Huang, Hui Zhao, Yuan Raviram, Ramya Gorkin, David U. Zhang, Yanxiao Sos, Brandon C. Afzal, Veena Dickel, Diane E. Kuan, Samantha Visel, Axel Pennacchio, Len A. Zhang, Kun Ren, Bing Ludwig Institute for Cancer Research La Jolla CA USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego School of Medicine La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Biomedical Sciences Graduate Program University of California San Diego La Jolla CA USA Department of Bioengineering University of California San Diego La Jolla CA USA Environmental Genomics and Systems Biology Division Lawrence Berkeley National Laboratory Berkeley CA USA US Department of Energy Joint Genome Institute Walnut Creek CA USA School of Natural Sciences University of California Merced Merced CA USA Comparative Biochemistry Program University of California Berkeley Berkeley CA USA Institute of Genomic Medicine Moores Cancer Center University of California San Diego School of Medicine La Jolla CA USA

Analysis of chromatin accessibility can reveal transcriptional regulatory sequences, but heterogeneity of primary tissues poses a significant challenge in mapping the precise chromatin landscape in specific cell types. Here we report single-nucleus ATAC-seq, a combinatorial barcoding-assisted single-cell assay for transposase-accessible chromatin that is optimized for use on flash-frozen primary tissue samples. We apply this technique to the mouse forebrain through eight developmental stages. Through analysis of more than 15,000 nuclei, we identify 20 distinct cell populations corresponding to major neuronal and non-neuronal cell types. We further define cell-type-specific transcriptional regulatory sequences, infer potential master transcriptional regulators and delineate developmental changes in forebrain cellular composition. Our results provide insight into the molecular and cellular dynamics that underlie forebrain development in the mouse and establish technical and analytical frameworks that are broadly applicable to other heterogeneous tissues.

关键词： Cell type diversity Chromatin Chromatin analysis Epigenomics

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High-Resolution Imaging of Human Viruses in Liquid Droplets

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Advanced materials (Deerfield Beach, Fla.) 2021年第37期33卷 e2103221页

作者： G M Jonaid William J Dearnaley Michael A Casasanta Liam Kaylor Samantha Berry Madeline J Dukes Michael S Spilman Jennifer L Gray Deborah F Kelly Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Department of Biomedical Engineering Pennsylvania State University University Park PA 16802 USA. Materials Research Institute Pennsylvania State University University Park PA 16802 USA. Center for Structural Oncology Pennsylvania State University University Park PA 16802 USA. Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA 16802 USA. Protochips Inc. Morrisville NC 27560 USA. Direct Electron LP. San Diego CA 92128 USA.

Liquid-phase electron microscopy (LP-EM) is an exciting new area in the materials imaging field, providing unprecedented views of molecular processes. Time-resolved insights from LP-EM studies are a strong complement to the remarkable results achievable with other high-resolution techniques. Here, the opportunities to expand LP-EM technology beyond 2D temporal assessments and into the 3D regime are described. The results show new structures and dynamic insights of human viruses contained in minute volumes of liquid while acquired in a rapid timeframe. To develop this strategy, adeno-associated virus (AAV) is used as a model system. AAV is a well-known gene therapy vehicle with current applications involving drug delivery and vaccine development for COVID-19. Improving the understanding of the physical properties of biological entities in a liquid state, as maintained in the human body, has broad societal implications for human health and disease.

关键词： COVID-19 SARS-CoV-2 adeno-associated virus direct electron detector liquid-phase electron microscopy silicon nitride

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Non-Native Species in Aquaculture: Burgeoning Production and Environmental Sustainability Risks

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Reviews in Aquaculture 2025年第3期17卷

作者： Francisco J. Oficialdegui Ismael Soto Paride Balzani Ross N. Cuthbert Phillip J. Haubrock Melina Kourantidou Eléna Manfrini Ali Serhan Tarkan Irmak Kurtul Rafael L. Macêdo Camille L. Musseau Koushik Roy Antonín Kouba Faculty of Fisheries and Protection of Waters South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses University of South Bohemia in České Budějovice Vodňany Czech Republic Institute for Global Food Security School of Biological Sciences Queen's University Belfast Belfast UK Faculty of Science and Technology Department of Life and Environmental Sciences Bournemouth University Dorset UK CAMB Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Hawally Kuwait Department of Business and Sustainability University of Southern Denmark Esbjerg Ø Denmark EMR 6004 AMURE CNRS University of Brest Ifremer IRD Plouzané France Unité Biologie des Organismes et Ecosystèmes Aquatiques (BOREA UMR 8067) Muséum National d'Histoire Naturelle Sorbonne Universités Université de Caen Normandie Université des Antilles CNRS IRD Paris France Agroparistech Ecologie Systématique Evolution Université Paris Saclay CNRS Gif-sur-Yvette France University of Lodz Faculty of Biology and Environmental Protection Department of Ecology and Vertebrate Zoology Łódź Poland Faculty of Fisheries Department of Aquatic Basic Science Muğla Sıtkı Koçman University Muğla Türkiye Faculty of Fisheries Marine and Inland Waters Sciences and Technology Department Ege University İzmir Türkiye Institute of Biology Freie Universität Berlin Berlin Germany Department of Evolutionary and Integrative Ecology Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) Berlin Germany Graduate Program in Ecology and Natural Resources Department of Ecology and Evolutionary Biology Federal University of São Carlos UFSCar São Carlos Brazil Department of Fish Biology Fisheries and Aquaculture Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) Berlin Germany

Rising global food demands and technological advancements have led to unprecedented growth in the aquaculture industry. This rapid expansion has facilitated the translocation of species beyond their native ranges. While farming non-native species boosts global food supply, it also poses environmental and socio-economic risks when escapees establish in non-native ecosystems. Using FAO data, we quantified and analysed global non-native aquaculture production, economic value, and monetary costs over space and time. Since 1950, one-third of the 560 species used in aquaculture ( n = 160) have been farmed outside of their native ranges, totaling 571.6 million tonnes valued at USD 1.2 trillion. Both native and non-native production increased over time, with non-native species showing greater interannual variability. Fishes largely dominated total aquaculture production with 940 million tonnes, of which 182 million tonnes were non-native production (19%). Non-native algae and crustacean production exceeded that of native species, accounting for 67% and 55% of total production, respectively. Notably, non-native crustacean production has grown enormously in recent years, with a rate of change of over 11,000% since 2000, compared to the previous two decades. According to the InvaCost database, 27 non-native species have been associated with reported monetary costs due to their impacts as invasive species. Among them, nine major aquaculture species documented at least USD 6.4 billion in global total costs. To address the rising threats of biological invasions triggered by aquaculture escapees, enhanced biosecurity, stakeholder awareness, and promotion of sustainable use of native resource alternatives are needed.

关键词： aquaculture production biological invasions environmental impact externality introduction pathway

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Towards Better and More Valid Zebrafish Models of Alzheimer's Disease: A Scientific Tribute to Prof. Mikhail I. Aghajanov

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Journal of neurochemistry 2025年第6期169卷

作者： Maria M Kotova Adam Michael Stewart Artem Grigoryan Sanobar Shariff Foad Mirzaei Burhan Kantawala Karen Dilbaryan Murilo S de Abreu David S Galstryan Jiahao Cui Longen Yang Konstantin B Yenkoyan Allan V Kalueff Neurobiology Program Scientific Center for Genetics and Life Sciences Sirius University of Science and Technology Sochi Russia. The International Zebrafish Neuroscience Research Consortium (ZNRC) New Orleans Louisiana USA. The International Stress and Behavior Society (ISBS) New Orleans Louisiana USA. Neuroscience Laboratory COBRAIN Center Yerevan State Medical University named after Mkhitar Heratsi Yerevan Armenia. Graduate Program in Health Sciences Federal University of Health Sciences of Porto Alegre Porto Alegre Brazil. Institute of Translational Biomedicine St. Petersburg State University St. Petersburg Russia. Institute of Experimental Medicine Almazov National Medical Research Center Ministry of Health of Russian Federation St. Petersburg Russia. World Class Research Center for Personalized Medicine Almazov National Medical Research Centre Ministry of Healthcare of Russian Federation St. Petersburg Russia. Department of Biosciences and Bioinformatics School of Science Xi'an Jiaotong-Liverpool University Suzhou China. Suzhou Key Laboratory on Neurobiology and Cell Signaling School of Science Xi'an Jiaotong-Liverpool University Suzhou China. Deparment of Biochemistry Yerevan State Medical University named after Mkhitar Heratsi Yerevan Armenia.

The most common form of dementia, Alzheimer's disease (AD) is a severely debilitating neurodegenerative disorder that afflicts over 50 million people globally. Despite extensive its research using various animal models, nearly all promising AD treatments have failed in clinical trials. Zebrafish (Danio rerio) have recently emerged as a valuable alternative to traditional (rodent) models of AD, possessing conserved neurotransmitter systems and disease pathways with humans, as well as orthologs for key genes associated with neurodegenerative disease. Here, we review recent advances and applications of zebrafish to study the pathogenesis of AD, and discuss the advantages, limitations, and potential future directions of research utilizing zebrafish AD models. This paper is dedicated to the late Professor Mikhail I. Aghajanov (1939-2024), a prominent Armenian neurochemist and a true crusader for fundamental AD research.

关键词： Alzheimer's disease animal model dementia neurodegeneration zebrafish

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Pandemics are catalysts of scientific novelty: Evidence from COVID-19

arXiv

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arXiv 2020年

作者： Liu, Meijun Bu, Yi Chen, Chongyan Xu, Jian Li, Daifeng Leng, Yan Freeman, Richard Barry Meyer, Eric Yoon, Wonjin Sung, Mujeen Jeong, Minbyul Lee, Jinhyuk Kang, Jaewoo Min, Chao Song, Min Zhai, Yujia Ding, Ying Institute for Global Public Policy Fudan University Shanghai China Department of Information Management Peking University Beijing China School of Information University of Texas at Austin AustinTX United States School of Information Management Sun Yat-Sen University Guangzhou China McCombs School of Business University of Texas at Austin AustinTX United States Department of Economics Harvard University CambridgeMA United States CambridgeMA United States Department of Computer Science and Engineering Korea University Seoul Korea Republic of Interdisciplinary Graduate Program in Bioinformatics Korea University Seoul Korea Republic of School of Information Management Nanjing University Nanjing China Department of Library and Information Science Yonsei University Seoul Korea Republic of Department of Information Resource Management School of Management Tianjin Normal University Tianjin China School of Information Management Wuhan University Wuhan China Dell Medical School University of Texas at Austin AustinTX United States

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First-time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pre-trained on 29 million PubMed articles, and first-time collaboration increased after the outbreak of COVID-19, and international collaboration witnessed a sudden decrease. During COVID-19, papers with more first-time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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Author Correction: Widespread exposure to SARS-CoV-2 in wildlife communities

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Nature communications 2024年第1期15卷 6940页

作者： Amanda R Goldberg Kate E Langwig Katherine L Brown Jeffrey M Marano Pallavi Rai Kelsie M King Amanda K Sharp Alessandro Ceci Christopher D Kailing Macy J Kailing Russell Briggs Matthew G Urbano Clinton Roby Anne M Brown James Weger-Lucarelli Carla V Finkielstein Joseph R Hoyt Department of Biological Sciences Virginia Tech Blacksburg VA USA. Virginia Tech Carilion School of Medicine Virginia Tech Roanoke VA USA. Center for Emerging Zoonotic and Arthropod-borne Pathogens Virginia Tech Blacksburg VA USA. Molecular Diagnostics Laboratory Fralin Biomedical Research Institute Virginia Tech Roanoke VA USA. Department of Biomedical Sciences and Pathobiology Virginia Tech Blacksburg VA USA. Translational Biology Medicine and Health Graduate Program Virginia Tech Roanoke VA USA. Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg VA USA. Department of Biochemistry Virginia Tech Blacksburg VA USA. Data Services University Libraries Virginia Tech Blacksburg VA USA. Virginia Tech Center for Drug Discovery Virginia Tech Blacksburg VA USA. Academy of Integrated Science Virginia Tech Blacksburg VA USA. Department of Biological Sciences Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Virginia Tech Carilion School of Medicine Virginia Tech Roanoke VA USA. finkielc@vt.edu. Center for Emerging Zoonotic and Arthropod-borne Pathogens Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Molecular Diagnostics Laboratory Fralin Biomedical Research Institute Virginia Tech Roanoke VA USA. finkielc@vt.edu. Virginia Tech Center for Drug Discovery Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Academy of Integrated Science Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Department of Biological Sciences Virginia Tech Blacksburg VA USA. hoytjosephr@***.

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Transfer Learning from Chest X-Ray Pre-trained Convolutional Neural Network for Learning Mammogram Data

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Procedia Computer Science 2018年 135卷 400-407页

作者： Bens Pardamean Tjeng Wawan Cenggoro Reza Rahutomo Arif Budiarto Ettikan Kandasamy Karuppiah Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 NVIDIA Corporation

Breast cancer is one of the deadliest cancer for female nowadays. Despite of the rapid advancement in medical image analysis with the rise of deep learning, development of breast cancer detection system is limited due to relatively small size of the publicly available mammogram dataset. In this paper, we discover an effective configuration for transfer learning from Chest X-Ray pre-trained Convolutional Neural Network to overcome the small-size mammogram dataset problem. We found that the best configuration achieve 90.38% validation accuracy for modified.

关键词： Transfer learning Convolutional neural network Medical image analysis Chest X-ray Mammogram

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