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Correction to: Primary antibody deficiencies in Turkey: molecular and clinical aspects

Immunologic research 2022年第1期70卷 134页

作者： Sinem Firtina Yuk Yin Ng Ozden H Ng Ayca Kiykim Esra Yucel Ozek Manolya Kara Elif Aydiner Serdar Nepesov Yildiz Camcioglu Esra H Sayar Ezgi Yalcin Gungoren Ismail Reisli Selda H Torun Sule Haskologlu Tuba Cogurlu Aysenur Kaya Sukru Cekic Safa Baris Ugur Ozbek Ahmet Ozen Muge Sayitoglu Istanbul University Graduate School of Health Sciences Istanbul Turkey. Department of Bioinformatics and Genetics Engineering and Natural Sciences Faculty Istinye University Istanbul Turkey. Department of Genetics and Bioengineering Istanbul Bilgi University Istanbul Turkey. Department of Medical Biology Acibadem School of Medicine Acibadem Mehmet Ali Aydinlar University Istanbul Turkey. Department of Infectious Diseases and Clinical Immunology Cerrahpasa School of Medicine Istanbul University Istanbul Turkey. Department of Clinical Immunology Istanbul School of Medicine Istanbul University Istanbul Turkey. Istinye University Faculty of Medicine VM MedicalPark Pendik Hospital Pediatric Infectious Diseases Clinic Istanbul Turkey. Department of Pediatric Allergy and Immunology Marmara University Istanbul Turkey. Department of Pediatric Allergy Immunology Medipol University Istanbul Turkey. Department of Pediatric Immunology and Allergy Meram Medical Faculty Necmettin Erbakan University Konya Turkey. Department of Pediatric Immunology and Allergy Ankara University School of Medicine Ankara Turkey. Department of Pediatric Immunology and Allergy Kocaeli University Kocaeli Turkey. Department of Pediatric Immunology Uludag University School of Medicine Bursa Turkey. Department of Medical Genetics Acibadem School of Medicine Acibadem Mehmet Ali Aydinlar University Istanbul Turkey. Istanbul University Graduate School of Health Sciences Istanbul Turkey. mugeay@istanbul.edu.tr. Department of Genetics Aziz Sancar Institute of Experimental Medical Research Istanbul University Istanbul Turkey. mugeay@istanbul.edu.tr.

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Nuclear lamina maintains global spatial organization of chromatin in Drosophila cultured cells

Nuclear lamina maintains global spatial organization of chro...

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IEEE International Conference on bioinformatics and Biomedicine

作者： Sergey V. Ulianov Semen A. Doronin Ekaterina E. Khrameeva Pavel I. Kos Sergey S. Starikov Aleksandra A. Galitsyna Artem Luzhin Mikhail S. Gelfand Alexander V. Chertovich Sergey V. Razin Yuri Y. Shevelyov Russian Academy of Sciences Institute of Gene Biology Moscow Russia Russian Academy of Sciences Institute of Molecular Genetics Moscow Russia Russian Academy of Sciences Institute for Information Transmission Problems (the Kharkevich Institute) Moscow Russia Faculty of Physics M.V. Lomonosov Moscow State University Moscow Russia Faculty of Bioengineering and Bioinformatics M.V. Lomonosov Moscow State University Moscow Russia

ISBN: (纸本)9781538654897;9781538654880

Interphase chromatin in animals is constrained by interactions with the nuclear lamina (NL) - a protein mesh lining nuclear envelope and composed from lamins and lamin-associated proteins. About 30% of chromatin is located near the NL in a living cell forming densely packed lamina-associated domains (LADs). LADs largely overlap with topologically-associating domains (TADs) build up from repressed chromatin, and contain predominately inactive genes, thus playing a role in transcription regulation. Here, we show that the NL disruption in Drosophila leads to en mass chromatin compactisation and redistribution towards the nuclear interior. This results in an increase of contact frequency between active and repressed fractions of the genome accompanied by the transcription upregulation in LADs. A subset of TADs characterized by high level of LADs become less compact, that could be driven by the loss of interactions with the nuclear envelope as revealed by polymer modelling. These results indicate that the NL in Drosophila cells plays a role in the specific spatial positioning of the chromatin inside the nucleus, its compartmentalization and at least partially controls the packaging density and low-level transcription in LADs.

关键词： Conferences bioinformatics

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The accuracy of the rapid equilibrium assumption in steady-state enzyme kinetics in the case of a multipath arbitrary enzyme mechanism with a number of equilibrium segments

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Biophysics (Russian Federation) 2016年第3期61卷 373-379页

作者： Vrzheshch, P.V. Faculty of Bioengineering and Bioinformatics Moscow State University International Biotechnological Center Moscow 119991 Russian Federation

A quantitative evaluation of the accuracy of the rapid-equilibrium assumption in steady-state enzyme kinetics was obtained for a multipath arbitrary enzyme mechanism with a number of equilibrium segments. Explicit expressions for estimating the contribution of any equilibrium segment to the accuracy of the rapid-equilibrium assumption were obtained. This allowed us to determine the accuracy of the rapid-equilibrium assumption (Δ) in general: 1 + Δ = (1 + Δ₁)(1 + Δ₂).. (1 + Δ_k), where Δ₁, Δ₂,.., Δ_k is the contribution of each individual equilibrium segment. The accuracy depends only on the structure and properties of equilibrium segments, which have been accounted for in the rapid-equilibrium assumption, but it is independent of the number of paths in the mechanism of the enzymatic reaction and on the structure and properties of the remaining part (steady-state) of the kinetic scheme. © 2016, Pleiades Publishing, Inc.

关键词： accuracy of assumption equilibrium segments graph theory multipath enzyme mechanisms rapid-equilibrium assumption steady-state enzyme kinetics

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Author Correction: A virally encoded tRNA neutralizes the PARIS antiviral defence system

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Nature 2024年第8043期636卷 E8页

作者： Nathaniel Burman Svetlana Belukhina Florence Depardieu Royce A Wilkinson Mikhail Skutel Andrew Santiago-Frangos Ava B Graham Alexei Livenskyi Anna Chechenina Natalia Morozova Trevor Zahl William S Henriques Murat Buyukyoruk Christophe Rouillon Baptiste Saudemont Lena Shyrokova Tatsuaki Kurata Vasili Hauryliuk Konstantin Severinov Justine Groseille Agnès Thierry Romain Koszul Florian Tesson Aude Bernheim David Bikard Blake Wiedenheft Artem Isaev Department of Microbiology and Cell Biology Montana State University Bozeman MT USA. The Center for Molecular and Cellular Biology Moscow Russia. Synthetic Biology Institut Pasteur Université Paris Cité CNRS UMR 6047 Paris France. Center for Precision Genome Editing and Genetic Technologies for Biomedicine Institute of Gene Biology Russian Academy of Sciences Moscow Russia. Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia. Peter the Great St Petersburg State Polytechnic University St. Petersburg Russia. Department of Experimental Medical Science Lund University Lund Sweden. Virus Centre Lund University Lund Sweden. Science for Life Laboratory Lund Sweden. Waksman Institute Rutgers The State University of New Jersey Piscataway NJ USA. Unité Régulation Spatiale des Génomes Institut Pasteur CNRS UMR 3525 Université Paris Cité Paris France. Center for Interdisciplinary Research in Biology (CIRB) Collège de France CNRS INSERM Université PSL Paris France. Collège Doctoral Sorbonne Université Paris France. Molecular Diversity of Microbes Institut Pasteur CNRS UMR3525 Université Paris Cité Paris France. Synthetic Biology Institut Pasteur Université Paris Cité CNRS UMR 6047 Paris France. david.bikard@pasteur.fr. Department of Microbiology and Cell Biology Montana State University Bozeman MT USA. bwiedenheft@***. The Center for Molecular and Cellular Biology Moscow Russia. tcft18@***.

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Improved Metaheuristic Algorithms for Metabolic Network Optimization

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IOP Conference Series: Materials Science and Engineering 2019年第1期551卷

作者： K Mohd Daud Z Zakaria R Hassan M S Mohamad Z Ali Shah Artificial Intelligence and Bioinformatics Research Group School of Computing Faculty of Engineering Universiti Teknologi Malaysia 81310 Johor Bahru Malaysia Software Engineering Department School of Computing Faculty of Engineering Universiti Teknologi Malaysia 81310 Johor Bahru Malaysia Institute for Artificial Intelligence and Big Data Universiti Malaysia Kelantan City Campus Pengkalan Chepa 16100 Kota Bharu Kelantan Malaysia Faculty of Bioengineering and Technology Universiti Malaysia Kelantan Jeli Campus Lock Bag 100 17600 Jeli Kelantan Malaysia

Metaheuristic algorithms have been used in various domains to solve the optimization problem. In metabolic engineering, the problem of identifying near-optimal reactions knockout that can optimize the production rate of desired metabolites are hindered by the complexity of the metabolic networks. Through Flux Balance Analysis, different metaheuristics algorithms have been improved to optimize the desired phenotypes. In this paper, a comparative study of four metaheuristic algorithms have been proposed. Differential Search Algorithm (DSA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Genetic Algorithm (GA) are considered. These algorithms are tested on succinic acid production in Escherichia coli. The comparative performances are measured based on production rate, growth rate, and computational time. Hence, from the results, the best metaheuristic algorithms to solve the metabolic network optimization is identified.

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Molecular mechanisms of ischemic kidney injury and protection: the role of mitochondria

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Biochimica et Biophysica Acta (BBA) - Bioenergetics 2018年 1859卷 e55-e56页

作者： Nadezda V. Andrianova Stanislovas S. Jankauskas Ljubava D. Zorova Irina B. Pevzner Vasily A. Popkov Denis N. Silachev Dmitry B. Zorov Egor Y. Plotnikov Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia Belozersky Institute of Physico-Chemical Biology Lomonosov Moscow State University Moscow Russia

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Mitochondrial uncouplers induce CpG methylation of the ICAM1 gene promoter in endothelial cells

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Biochimica et Biophysica Acta (BBA) - Bioenergetics 2018年 1859卷 e119-e119页

作者： Roman A. Zinovkin Anastasia I. Kalashnikova Anastasia S. Prikhodko Ludmila A. Zinovkina Belozersky Institute of Physico-Chemical Biology Lomonosov Moscow State University Moscow Russia Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia

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AbdomenCT-1K: Is abdominal organ segmentation a solved problem?

arXiv

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arXiv 2020年

作者： Ma, Jun Zhang, Yao Gu, Song Zhu, Cheng Ge, Cheng Zhang, Yichi An, Xingle Wang, Congcong Wang, Qiyuan Liu, Xin Cao, Shucheng Zhang, Qi Liu, Shangqing Wang, Yunpeng Li, Yuhui He, Jian Yang, Xiaoping Department of Mathematics Nanjing University of Science and Technology China Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences China AI Lab Lenovo Research School of Automation Nanjing University of Information Science and Technology China Shenzhen Haichuang Medical CO. LTD. China Institute of Bioinformatics and Medical Engineering Jiangsu University of Technology China School of Biological Science and Medical Engineering Beihang University China Beijing Infervision Technology CO. LTD. China School of Computer Science and Engineering Tianjin University of Technology China Department of Computer Science Norwegian University of Science and Technology Norway School of Electronic Science and Engineering Nanjing University China Suzhou LungCare Medical Technology Co. Ltd China Bioengineering Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Computer and Information Science Faculty of Science and Technology University of Macau China School of Biomedical Engineering Southern Medical University China Institutes of Biomedical Sciences Fudan University China Computational Biology University of Southern California United States Department of Radiology Nanjing Drum Tower Hospital The Affiliated Hospital Nanjing University Medical School China Department of Mathematics Nanjing University China

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets. However, most of the existing abdominal datasets only contain single-center, single-phase, single-vendor, or single-disease cases, and it is unclear whether the excellent performance can generalize on diverse datasets. This paper presents a large and diverse abdominal CT organ segmentation dataset, termed AbdomenCT-1K, with more than 1000 (1K) CT scans from 12 medical centers, including multi-phase, multi-vendor, and multi-disease cases. Furthermore, we conduct a large-scale study for liver, kidney, spleen, and pancreas segmentation and reveal the unsolved segmentation problems of the SOTA methods, such as the limited generalization ability on distinct medical centers, phases, and unseen diseases. To advance the unsolved problems, we further build four organ segmentation benchmarks for fully supervised, semi-supervised, weakly supervised, and continual learning, which are currently challenging and active research topics. Accordingly, we develop a simple and effective method for each benchmark, which can be used as out-of-the-box methods and strong baselines. We believe the AbdomenCT-1K dataset will promote future in-depth research towards clinical applicable abdominal organ segmentation methods. © 2020, CC BY-NC-SA.

关键词： Computerized tomography

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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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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