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arXiv 2024年

作者： Akiyama, Kazunori Niinuma, Kotaro Hada, Kazuhiro Doi, Akihiro Hagiwara, Yoshiaki Higuchi, Aya E. Honma, Mareki Kawashima, Tomohisa Kolev, Dimitar Koyama, Shoko Masui, Sho Ohsuga, Ken Sano, Hidetoshi Takami, Hideki Tsunetoe, Yuh Uzawa, Yoshinori Akahori, Takuya Akiyama, Yuto Galison, Peter Hayashi, Takayuki J. Hirota, Tomoya Inoue, Makoto Iwata, Yuhei Johnson, Michael D. Kino, Motoki Kofuji, Yutaro Mizuno, Yosuke Moriyama, Kotaro Nagai, Hiroshi Nakamura, Kenta Notsu, Shota Ono, Fumie Oya, Yoko Oyama, Tomoaki Rana, Hannah Saida, Hiromi Saito, Ryo Saito, Yoshihiko Sasada, Mahito Sawada-Satoh, Satoko Takahashi, Mikiya M. Takamura, Mieko Tong, Edward Tsuji, Hiroyuki Yoshioka, Shogo Watanabe, Yoshimasa Massachusetts Institute of Technology Haystack Observatory WestfordMA01886 United States Mizusawa VLBI Observatory National Astronomical Observatory of Japan Iwate023-0861 Japan Black Hole Initiative Harvard University CambridgeMA02138 United States Graduate School of Sciences and Technology for Innovation Yamaguchi University Yamaguchi753-8512 Japan The Graduate School of Science Nagoya City University Aichi467-0001 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Kanagawa252-5210 Japan Department of Space and Astronautical Science The Graduate University for Advanced Studies SOKENDAI Kanagawa229-8510 Japan Natural Science Laboratory Toyo University Tokyo112-8606 Japan Division of Science School of Science and Engineering Tokyo Denki University Saitama350-0394 Japan Department of Astronomy Graduate School of Science The University of Tokyo Tokyo113-0033 Japan Institute for Cosmic Ray Research The University of Tokyo Chiba277-8582 Japan Space Communication Systems Laboratory Wireless Networks Research Center National Institute of Information and Communications Technology Tokyo184-8795 Japan Graduate School of Science and Technology Niigata University Niigata950-2181 Japan Advanced Technology Center National Astronomical Observatory of Japan Tokyo181-8588 Japan Center for Computational Sciences University of Tsukuba Ibaraki305-8577 Japan Faculty of Engineering Gifu University Gifu501-1193 Japan Harvard University CambridgeMA02138 United States Azabu Junior and Senior High School Tokyo106-0046 Japan Astronomical Science Program The Graduate University for Advanced Studies SOKENDAI Tokyo181-8588 Japan Institute of Astronomy and Astrophysics Academia Sinica Taipei10617 Taiwan Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States Kogakuin University of Technology & Engineering Academic Support Center 2665-1 Nakano Hachioji Tokyo192-0015 Japan Tsung-Dao Lee Institut

The Black Hole Explorer (BHEX) is a next-generation space very long baseline interferometry (VLBI) mission concept that will extend the ground-based millimeter/submillimeter arrays into space. The mission, closely aligned with the science priorities of the Japanese VLBI community, involves an active engagement of this community in the development of the mission, resulting in the formation of the Black Hole Explorer Japan Consortium. Here we present the current Japanese vision for the mission, ranging from scientific objectives to instrumentation. The Consortium anticipates a wide range of scientific investigations, from diverse black hole physics and astrophysics studied through the primary VLBI mode, to the molecular universe explored via a potential single-dish observation mode in the previously unexplored 50-70 GHz band that would make BHEX the highest-sensitivity explorer ever of molecular oxygen. A potential major contribution for the onboard instrument involves supplying essential elements for its high-sensitivity dual-band receiving system, which includes a broadband 300 GHz SIS mixer and a space-certified multi-stage 4.5K cryocooler akin to those used in the Hitomi and XRISM satellites by the Japan Aerospace Exploration Agency. Additionally, the Consortium explores enhancing and supporting BHEX operations through the use of millimeter/submillimeter facilities developed by the National Astronomical Observatory of Japan, coupled with a network of laser communication stations operated by the National Institute of Information and Communication Technology. Copyright © 2024, The Authors. All rights reserved.

关键词： Radio astronomy

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Corrigendum: Moving Next-Generation Phase-Field Models to BMS Applications -A Case Study that Confirms Professor Uzi Landau's Foresight [J. Electrochem. Soc., 171, 063507 (2024)]

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Journal of The Electrochemical Society 2024年第8期171卷 089002-089002页

作者： Tushar K. Telmasre Anthony César Concepción Suryanarayana Kolluri Lubhani Mishra Raghav S. Thiagarajan Aditya Naveen Matam Akshay Subramaniam Taylor R. Garrick Venkat R. Subramanian Materials Science and Engineering Program Texas Materials Institute The University of Texas at Austin Austin TX 78712 United States of America Walker Department of Mechanical Engineering The University of Texas at Austin Austin TX 78712 United States of America Battery Materials and Systems Research General Motors Global Research and Development Center Warren MI 48090 United States of America Chandra Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 United States of America Energy Storage and Propulsion R&D and Manufacturing Engineering General Motors Technical Center Warren MI 48092 United States of America Affiliate Faculty Oden Institute for Computational Science and Engineering The University of Texas at Austin Austin TX 78712 United States of America

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QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data

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Current Protocols in Bioinformatics 2020年第1期70卷 e100页

作者： Estaki, Mehrbod Jiang, Lingjing Bokulich, Nicholas A. McDonald, Daniel González, Antonio Kosciolek, Tomasz Martino, Cameron Zhu, Qiyun Birmingham, Amanda Vázquez-Baeza, Yoshiki Dillon, Matthew R. Bolyen, Evan Caporaso, J. Gregory Knight, Rob Department of Pediatrics University of California San Diego La Jolla CA United States Division of Biostatistics University of California San Diego La Jolla CA United States Center for Applied Microbiome Science Pathogen and Microbiome Institute Northern Arizona University Flagstaff AZ United States Department of Biological Sciences Northern Arizona University Flagstaff AZ United States Małopolska Centre of Biotechnology Jagiellonian University Kraków Poland Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA United States Center for Microbiome Innovation University of California San Diego La Jolla CA United States Center for Computational Biology and Bioinformatics University of California San Diego La Jolla CA United States Jacobs School of Engineering University of California San Diego La Jolla CA United States Department of Computer Science and Engineering University of California San Diego La Jolla CA United States Department of Bioengineering University of California San Diego La Jolla CA United States

QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses—e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://***. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://***. © 2020 The Authors. Basic Protocol: Using QIIME 2 with microbiome data. Support Protocol: Further microbiome analyses. © 2020 The Authors.

关键词： bioinformatics metagenomics microbiome QIIME 2 Qiita

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Molecular landscape of sex- and modality-specific exercise adaptation in human skeletal muscle through large-scale multi-omics integration

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Cell Reports 2025年第6期44卷 115750页

作者： Macsue Jacques Shanie Landen Adam P. Sharples Andrew Garnham Ralf Schittenhelm Joel Steele Aino Heikkinen Elina Sillanpää Miina Ollikainen James Broatch Navabeh Zarekookandeh Ola Hanson Ola Ekström Olof Asplund Séverine Lamon Sarah E. Alexander Cassandra Smith Carlie Bauer Mary N. Woessner Itamar Levinger Andrew E. Teschendorff Linn Gillberg Ida Blom Jørn Wulff Helge Nicholas R. Harvey Larisa M. Haupt Lyn R. Griffiths Atul S. Deshmukh Kirsi H. Pietiläinen Päivi Piirilä Robert A.E. Seaborne Marie Klevjer Anja Bye Ulrik Wisløff Bernadette Jones-Freeman Nir Eynon Australian Regenerative Medicine Institute Monash University Clayton VIC Australia Institute for Health and Sport (iHeS) Victoria University Footscray VIC Australia Centre for Endocrinology and Metabolism Hudson Institute of Medical Research Melbourne VIC Australia Institute of Physical Performance Norwegian School of Sport Sciences Oslo Norway Monash Proteomics & Metabolomics Platform Monash Biomedicine Discovery Institute Monash University Melbourne VIC Australia Institute for Molecular Medicine Finland (FIMM) Helsinki University Helsinki Finland Faculty of Sport and Health Sciences University of Jyväskylä Jyväskylä Finland Wellbeing Services County of Central Finland Jyväskylä Finland Minerva Foundation Institute for Medical Research Helsinki Finland Department of Clinical Sciences Translational Muscle Research Unit Lund University Diabetes Center Lund University Lund Sweden Institute for Physical Activity and Nutrition (IPAN) School of Exercise and Nutrition Sciences Deakin University 221 Burwood Highway Burwood VIC 3125 Australia Cardiometabolic Health and Exercise Physiology Laboratory Baker Heart and Diabetes Institute 75 Commercial Road Melbourne VIC 3004 Australia Nutrition & Health Innovation Research Institute Edith Cowan University Joondalup WA Australia Medical School The University of Western Australia Perth WA Australia Australian Institute for Musculoskeletal Science (AIMSS) Victoria University Melbourne VIC Australia CAS Key Lab of Computational Biology Shanghai Institute of Nutrition and Health Shanghai China Department of Biomedical Sciences University of Copenhagen Copenhagen Denmark Faculty of Health Sciences and Medicine Bond University Gold Coast QLD Australia Genomics Research Centre Centre for Genomics and Personalised Health School of Biomedical Sciences Queensland University of Technology Brisbane QLD Australia ARC Training Centre for Cell and Tissue Engineering Technologies Queensland University of Technology (Q

We investigated the molecular mechanisms of exercise adaptations in human muscle by integrating genome, methylome, transcriptome, and proteome data from over 1,000 participants (2,340 muscle samples). We identified distinctive signatures associated with maximal oxygen consumption (VO2max), and multi-omics integration uncovered five key genes as robust exercise markers across layers, with transcription factors functioning as activators, synergizing with DNA methylation to regulate gene expression. Minimal sex differences were observed, while modality-specific analysis highlighted distinct pathways for aerobic and resistance exercise, contrasting with muscle disuse patterns. Finally, we created a webtool, OMAx, featuring our individual omics and integration analysis. These findings provide a comprehensive multi-omics framework for understanding exercise-induced molecular adaptations, offering insights into muscle health, cardiorespiratory fitness, and their roles in aging and disease prevention.

关键词： skeletal muscle Multi Omics epigenetics DNA methylation exercise VO2 max gene expression transcriptomic proteomic

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The bulk van der Waals layered magnet CrSBr is a quasi-1D material

arXiv

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arXiv 2022年

作者： Klein, Julian Pingault, Benjamin Florian, Matthias Heißenbüttel, Marie-Christin Steinhoff, Alexander Song, Zhigang Torres, Kierstin Dirnberger, Florian Curtis, Jonathan B. Weile, Mads Penn, Aubrey Deilmann, Thorsten Dana, Rami Bushati, Rezlind Quan, Jiamin Luxa, Jan Sofer, Zdenek Alù, Andrea Menon, Vinod M. Wurstbauer, Ursula Rohlfing, Michael Narang, Prineha Lončar, Marko Ross, Frances M. Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States QuTech Delft University of Technology Delft2600 GA Netherlands Department of Electrical and Computer Engineering Department of Physics University of Michigan Ann ArborMI48109 United States Institut für Festkörpertheorie Westfälische Wilhelms-Universität Münster Münster48149 Germany Institut für Theoretische Physik Universität Bremen P.O. Box 330 440 Bremen28334 Germany Bremen Center for Computational Materials Science University of Bremen Bremen28359 Germany Department of Physics City College of New York New YorkNY10031 United States College of Letters and Science UCLA Los AngelesCA90095 United States Department of Physics Technical University of Denmark Kgs. LyngbyDK-2800 Denmark MIT.nano Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics The Graduate Center City University of New York New YorkNY10016 United States Photonics Initiative CUNY Advanced Science Research Center New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10026 United States Department of Inorganic Chemistry University of Chemistry and Technology Prague Technická 5 Prague 6166 28 Czech Republic Institute of Physics Center for Nanotechnology University of Münster Münster48149 Germany

Correlated quantum phenomena in one-dimensional (1D) systems that exhibit competing electronic and magnetic order are of strong interest for studying fundamental interactions and excitations, such as Tomonaga-Luttinger liquids and topological orders and defects with properties completely different from the quasiparticles expected in their higher-dimensional counterparts. However, clean 1D electronic systems are difficult to realize experimentally, particularly magnetically ordered systems. Here, we show that the van der Waals layered magnetic semiconductor CrSBr behaves like a quasi-1D material embedded in a magnetically ordered environment. The strong 1D electronic character originates from the Cr-S chains and the combination of weak interlayer hybridization and anisotropy in effective mass and dielectric screening with an effective electron mass ratio of meX/meY ∼ 50. This extreme anisotropy experimentally manifests in strong electron-phonon and exciton-phonon interactions, a Peierls-like structural instability and a Fano resonance from a van Hove singularity of similar strength of metallic carbon nanotubes. Moreover, due to the reduced dimensionality and interlayer coupling, CrSBr hosts spectrally narrow (1 meV) excitons of high binding energy and oscillator strength that inherit the 1D character. Overall, CrSBr is best understood as a stack of weakly hybridized monolayers and appears to be an experimentally attractive candidate for the study of exotic exciton and 1D correlated many-body physics in the presence of magnetic order. Copyright © 2022, The Authors. All rights reserved.

关键词： Excitons

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems computational modeling

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Cover Image, Volume 86, Issue 5

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Proteins: Structure, Function, and Bioinformatics 2018年第5期86卷

作者： J. C. Gaines S. Acebes A. Virrueta M. Butler L. Regan C. S. O'Hern Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 Integrated Graduate Program in Physical and Engineering Biology (IGPPEB) Yale University New Haven Connecticut 06520 Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 Department of Physics and Astronomy University of Southern California Los Angeles California 90007 Department of Molecular Biophysics & Biochemistry Yale University New Haven Connecticut 06520 Department of Chemistry Yale University New Haven Connecticut 06520 Department of Physics Yale University New Haven Connecticut 06520 Department of Applied Physics Yale University New Haven Connecticut 06520

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Education for the future

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science 2018年第6396期360卷 1409-1412页

作者： Cheung, Man Kit Schwendimann, Beat A. Ward, Adrian Pietrzak, Barbara Mollaoglu, Gurkan Duong, Michael Tran Allareddy, Veerasathpurush Ulltveit-Moe, Nils Dutton-Regester, Ken Zhang, Jian Scult, Matthew A. Singh, Poonam C. Yan, Hong Young Naz, Saima Isaacson, Kyle Dennis, Allison F. Beardsley, Felicia Rounds Al-Humaidan, Eyad Ibrahim Lo, Cody Jones, Tyler Sood, Prashant Nieuwenhuis, Rense Ali, Basant A. Yu, Kun-Hsing Arthur, Patrick Kobina Kumar, Brijesh Buschke, Falko Chen, Alexander Cingl, Lubomír O’Mullane, Anthony Peter Coetzee, Vinet Zaidi, Syed Shan-e-Ali Konstantinides, Nikos School of Life Sciences Chinese University of Hong Kong Shatin New Territories Hong Kong Graduate School of Education University of California Berkeley Berkeley 94720 CA United States University of Queensland St. Lucia 4072 QLD Australia Department of Hydrobiology Faculty of Biology Biological and Chemical Research Centre University of Warsaw Warsaw 02-089 Poland Department of Oncological Sciences University of Utah School of Medicine Salt Lake City 84112 UT United States Perelman School of Medicine University of Pennsylvania Philadelphia 19104 PA United States University of Illinois College of Dentistry Chicago 60612 IL United States Department of Information and Communication Technology University of Agder 4879 Grimstad Norway Department of Genetics and Computational Biology QIMR Berghofer Medical Research Institute Brisbane 4006 QLD Australia School of Safety and Environmental Engineering Hunan Institute of Technology Hengyang Hunan 421002 China Lahore 54000 Punjab Pakistan Department of Psychology and Neuroscience Duke University Durham 27708 NC United States National Museum of Marine Biology and Aquarium Chercheng Pingtung County 94450 Taiwan Division of Plant Microbe Interactions CSIR–National Botanical Research Institute Lucknow 226001 Uttar Pradesh India Program in Cell Molecular Developmental Biology and Biophysics (CMDB) Johns Hopkins University Baltimore 21218 MD United States Stem Cell and Tissue Re-Engineering Program King Faisal Specialist Hospital and Research Centre Riyadh Saudi Arabia Department of Sociology and Anthropology University of La Verne La Verne 91750 CA United States Department of Bioengineering University of Utah Salt Lake City 84112 UT United States MRC Centre for Medical Mycology University of Aberdeen Aberdeen AB25 2ZD United Kingdom Faculty of Medicine University of British Columbia Vancouver V6T 1Z2 BC Canada School of Engineering Brown University Providence 02912 RI United States

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Nat Genet:单细胞分析解开结直肠癌细胞的神秘面纱

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现代生物医学进展 2017年第15期17卷 I0003-I0003页

作者： Huipeng Li, Elise T Courtois, Debarka Sengupta, Yuliana Tan Shyam Prabhakar Elise T Courtois, Yuliana Tan Paul Robson Debarka Sengupta Kok Hao Chen, Jolene Jie Lin Goh Paul Jongjoon Choi Say Li Kong, Axel M Hillmer Iain Beehuat Tan Clarinda Chua Iain Beehuat Tan Lim Kiat Hon Wah Siew Tan Mark Wong Lawrence J K Wee Iain Beehuat Tan Paul Robson Paul Robson Paul Robson Computational and Systems Biology Genome Institute of Singapore Singapore Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India Synthetic Biology Genome Institute of Singapore Singapore Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Department of Medical Oncology National Cancer Centre Singapore Singapore Department of Pathology Singapore General Hospital Singapore Department of Colorectal Surgery Singapore General Hospital Singapore Data Analytics Department Institute for Infocomm Research Singapore Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA Department of Biological Sciences National University of Singapore Singapore.

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测... 详细信息

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测序。”JAX科学家、这篇发表在Nature Genetics上的文章共同第一作者Elise Courtois说道。”我们可以根据肿瘤中的细胞组成将结直肠癌进一步分类。因为每种亚型的肿瘤病人生存率存在差别，我们的方法将为肿瘤医生提供更多的关于肿瘤预后和治疗的信息。”

关键词：单细胞分析结直肠癌癌细胞 Nat 细胞组成肿瘤病计算机技术细胞生物学

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Erratum to: The real cost of sequencing: scaling computation to keep pace with data generation

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Genome biology 2016年第1期17卷 78页

作者： Paul Muir Shantao Li Shaoke Lou Daifeng Wang Daniel J Spakowicz Leonidas Salichos Jing Zhang George M Weinstock Farren Isaacs Joel Rozowsky Mark Gerstein Department of Molecular Cellular and Developmental Biology Yale University New Haven CT 06520 USA. Systems Biology Institute Yale University West Haven CT 06516 USA. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. The Jackson Laboratory for Genomic Medicine Farmington CT 06032 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. mark@***. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. mark@***. Department of Computer Science Yale University New Haven CT 06520 USA. mark@***.

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