检索结果-内蒙古大学图书馆

arXiv 2017年

作者： VanderWerf, Kyle Jin, Weiwei Shattuck, Mark D. O'Hern, Corey S. Department of Physics Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department City College of New York New YorkNY10031 United States Department of Mechanics and Engineering Science Peking University Beijing100871 China Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

We perform computational studies of static packings of a variety of nonspherical particles including circulo-lines, circulo-polygons, ellipses, asymmetric dimers, dumbbells, and others to determine which shapes form packings with fewer contacts than degrees of freedom (hypostatic packings) and which have equal numbers of contacts and degrees of freedom (isostatic packings), and to understand why hypostatic packings of nonspherical particles can be mechanically stable despite having fewer contacts than that predicted from naïve constraint counting. To generate highly accurate force- and torque-balanced packings of circulo-lines and -polygons, we developed an interparticle potential that gives continuous forces and torques as a function of the particle coordinates. We show that the packing fraction and coordination number at jamming onset obey a master-like form for all of the nonspherical particle packings we studied when plotted versus the particle asphericity A, which is proportional to the ratio of the squared perimeter to the area of the particle. Further, the eigenvalue spectra of the dynamical matrix for packings of different particle shapes collapse when plotted at the same A. For hypostatic packings of nonspherical particles, we verify that the number of "quartic" modes along which the potential energy increases as the fourth power of the perturbation amplitude matches the number of missing contacts relative to the isostatic value. We show that the fourth derivatives of the total potential energy in the directions of the quartic modes remain nonzero as the pressure of the packings is decreased to zero. In addition, we calculate the principal curvatures of the inequality constraints for each contact in circulo-line packings and identify specific types of contacts with inequality constraints that possess convex curvature. These contacts can constrain multiple degrees of freedom and allow hypostatic packings of nonspherical particles to be mechanically stable. C

关键词： Degrees of freedom (mechanics)

来源：评论

学校读者我要写书评

暂无评论

Author Correction: Division of labour between Myc and G1 cyclins in cell cycle commitment and pace control

引用

Nature communications 2018年第1期9卷 4766页

作者： Peng Dong Manoj V Maddali Jaydeep K Srimani François Thélot Joseph R Nevins Bernard Mathey-Prevot Lingchong You Computational Biology and Bioinformatics Program Duke University Durham North Carolina 27708 USA. Department of Biomedical Engineering Duke University Durham North Carolina 27708 USA. School of Medicine Johns Hopkins University Baltimore Maryland 21205 USA. Department of Pharmacology and Cancer Biology Duke University Durham North Carolina 27708 USA. Department of Molecular Genetics and Microbiology Duke University Durham North Carolina 27708 USA. Department of Pharmacology and Cancer Biology Duke University Durham North Carolina 27708 USA. bernard.mathey-prevot@duke.edu. Department of Pediatrics Duke University Durham North Carolina 27708 USA. bernard.mathey-prevot@duke.edu. Department of Biomedical Engineering Duke University Durham North Carolina 27708 USA. you@duke.edu. Center for Genomic and Computational Biology Duke University Durham North Carolina 27708 USA. you@duke.edu. Duke Center for Systems Biology Duke University Durham North Carolina 27708 USA. you@duke.edu.

This Article contains errors in Supplementary Table 3, which are described in the Author Correction associated with this Article. The simulation results in the Article were based on the correct formula and thus the results are not affected by this correction. The errors have not been fixed in the original Article.

关键词：

来源：评论

学校读者我要写书评

暂无评论

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

引用

Nature genetics 2023年第9期55卷 1471-1482页

作者： Remi Stevelink Dorothee Kasteleijn-Nolst Trenite Bobby P. C. Koeleman Dick Lindhout Anja C. M. Sonsma Ciarán Campbell Gianpiero L. Cavalleri Norman Delanty Hany El-Naggar Austin Lacey Peter Widdess-Walsh Colin P. Doherty Siwei Chen Claire Churchhouse Mark J. Daly Yen-Chen A. Feng Daniel P. Howrigan Mitja I. Kurki Benjamin M. Neale Aarno Palotie Wei Zhou Namrata Gupta Henrike O. Heyne Bassel Abou-Khalil Kevin F. Haas R. S. Taneja Oluyomi M. Adesoji Michael Nothnagel Peter Nürnberg Thomas Sander Zaid Afawi Ilan Blatt Amos D. Korczyn Elisabetta Amadori Ganna Balagura Antonella Riva Marcello Scala Paolo Scudieri Pasquale Striano Federico Zara Michele Iacomino Francesca Madia Alison Anderson Patrick Kwan Terence J. O’Brien Slavé Petrovski K. Meng Tan Marian Todaro Joseph Anderson Danielle M. Andrade Quratulain Zulfiqar Ali Grazia Annesi Pauls Auce Andreja Avbersek Simona Balestrini Vera Braatz Claudia B. Catarino Krishna Chinthapalli Jennifer Jamnadas-Khoda Dalia Kasperavičiūte Costin Leu Josemir W. Sander Sanjay M. Sisodiya Sara Zagaglia Melanie Bahlo Karen L. Oliver Mark D. Baker Beata Fonferko-Shadrach William O. Pickrell Carmen Barba Claudia Bianchini Viola Doccini Renzo Guerrini Davide Mei Martino Montomoli Elena Parrini Annalisa Vetro Karen Barboza Fabrice Bartolomei Thomas Bast Bernhard J. Steinhoff Larry Baum Stacey S. Cherny Pak Sham Tobias Baumgartner Christian E. Elger Kerstin Hallmann Wolfram S. Kunz Rainer Surges Randi von Wrede Gábor Zsurka Betül Baykan Nerses Bebek Yeşim Kesim Albert J. Becker Susanne Schoch Felicitas Becker Caitlin A. Bennett Samuel F. Berkovic Stephanie L. Leech Brigid M. Regan Ingrid E. Scheffer Bianca Berghuis Ahmad Beydoun Wassim Nasreddine Francesca Bisulli Lidia Di Vito Lorenzo Ferri Tania Giangregorio Laura Licchetta Raffaella Minardi Barbara Mostacci Carlotta Stipa Paolo Tinuper Lorenzo Muccioli Federica Pondrelli Dheeraj R. Bobbili Emadeldin Hassanin Roland Krause Zied Landoulsi Patrick May Ingo Borggraefe Christian Bosselmann Christian Hengsbach Josua Kegele Stephen Lauxmann Department of Genetics University Medical Center Utrecht Utrecht The Netherlands Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede The Netherlands School of Pharmacy and Biomolecular Sciences The Royal College of Surgeons in Ireland Dublin Ireland The FutureNeuro Research Centre Dublin Ireland Department of Neurology Beaumont Hospital Dublin Ireland Department of Neurology St. James’s Hospital Dublin Ireland Analytic and Translational Genetics Unit Department of Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and M.I.T Cambridge MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Psychiatric & Neurodevelopmental Genetics Unit Department of Psychiatry Massachusetts General Hospital and Harvard Medical School Boston MA USA Division of Biostatistics Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Hasso Plattner Institute Digital Health Center University of Potsdam Potsdam Germany Hasso Plattner Institute Mount Sinai School of Medicine New York City NY USA Department of Neurology Vanderbilt University Medical Center Nashville TN USA Cologne Center for Genomics (CCG) University of Cologne Faculty of Medicine and University Hospital Cologne Cologne Germany University Hospital Cologne Cologne Germany Department of Neurology Charité Universitaetsmedizin Berlin Campus Virchow-Clinic Berlin Germany Tel-Aviv University Sackler Faculty of Medicine Ramat Aviv Israel Department of Neurology Sheba Medical Center Ramat Gan Israel Department of Neurosciences Rehabilitation Ophthalmology Genetics Maternal and Child Health University of Genova Genova Italy IRCCS Istituto Giannina Gaslini Genova Italy Department of Medicine University of Melbour

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information (vol 91, pg 626, 2022)

引用

BIOLOGICAL PSYCHIATRY 2022年第7期91卷 690-690页

作者： Maihofer, Adam X. Vinkers, Christiaan H. Department of Psychiatry University of California San Diego La Jolla California Department of Family Medicine and Public Health University of California San Diego La Jolla California Center of Excellence for Stress and Mental Health Veterans Affairs Healthcare System San Diego California. Electronic address: amaihofer@health.ucsd.edu. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts Department of Psychiatry Massachusetts General Hospital Boston Massachusetts. Social Genetic and Developmental Psychiatry Centre Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom National Institute of Health Research Maudsley Biomedical Research Centre King's College London London United Kingdom. Department of Psychiatry Harvard Medical School Boston Massachusetts Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge Massachusetts Center of Excellence in Depression and Anxiety Disorders Belmont Massachusetts. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge Massachusetts. Department of Psychiatry University of California San Diego La Jolla California Center of Excellence for Stress and Mental Health Veterans Affairs Healthcare System San Diego California Research Service Veterans Affairs Healthcare System San Diego California. Duke Molecular Physiology Institute Duke University School of Medicine Durham North Carolina. Department of Psychiatry Veterans Affairs Connecticut Healthcare System West Haven Connecticut Department of Psychiatry Yale University School of Medicine New Haven Connecticut. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts Department of Epidemiology Columbia University Mailman School of Public Health New York. Division of Mental Health Atlanta Veterans Affairs Medical Center

BACKGROUND: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). METHODS: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran program GWAS of PTSD total symptoms. RESULTS: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran program. CONCLUSIONS: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

关键词： GWAS Genetics Heritability PTSD PheWAS Trauma

来源：评论

学校读者我要写书评

暂无评论

Reprogramming Cancer Associated Fibroblasts as a therapeutic approach against Pancreatic Ductal Adenocarcinoma

引用

Pancreatology 2017年第3期17卷 S55-S55页

作者： Magdolna Djurec Kevin Troule Osvaldo Graña Albert Lee Raúl Rabadán Carmen Guerra Mariano Barbacid Molecular Oncology Centro Nacional de Investigaciones Oncológicas (CNIO) Madrid Spain Biotechnology Program Centro Nacional de Investigaciones Oncológicas (CNIO) Madrid Spain Center for Computational Biology and Bioinformatics Columbia University College of Physicians and Surgeons New York USA

来源：评论

学校读者我要写书评

暂无评论

Packing in protein cores

arXiv

引用

arXiv 2017年

作者： Gaines, J.C. Clark, A.H. Regan, L. O'Hern, C.S. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Yale University New HavenCT06520 United States Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Department of Molecular Biophysics & Biochemistry Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

Proteins are biological polymers that underlie all cellular functions. The first high-resolution protein structures were determined by x-ray crystallography in the 1960s. Since then, there has been continued interest in understanding and predicting protein structure and stability. It is well-established that a large contribution to protein stability originates from the sequestration from solvent of hydrophobic residues in the protein core. How are such hydrophobic residues arranged in the core? And how can one best model the packing of these residues? Here we show that to properly model the packing of residues in protein cores it is essential that amino acids are represented by appropriately calibrated atom sizes, and that hydrogen atoms are explicitly included. We show that protein cores possess a packing fraction of φ ≈ 0.56, which is significantly less than the typically quoted value of 0.74 obtained using the extended atom representation. We also compare the results for the packing of amino acids in protein cores to results obtained for jammed packings from disrete element simulations composed of spheres, elongated particles, and particles with bumpy surfaces. We show that amino acids in protein cores pack as densely as disordered jammed packings of particles with similar values for the aspect ratio and bumpiness as found for amino acids. Knowing the structural properties of protein cores is of both fundamental and practical importance. Practically, it enables the assessment of changes in the structure and stability of proteins arising from amino acid mutations (such as those identified as a result of the massive human genome sequencing efforts) and the design of new folded, stable proteins and protein-protein interactions with tunable specificity and affinity. Copyright © 2017, The Authors. All rights reserved.

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

Author Correction: Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

引用

Nature communications 2024年第1期15卷 2364页

作者： Celina Tretter Niklas de Andrade Krätzig Matteo Pecoraro Sebastian Lange Philipp Seifert Clara von Frankenberg Johannes Untch Gabriela Zuleger Mathias Wilhelm Daniel P Zolg Florian S Dreyer Eva Bräunlein Thomas Engleitner Sebastian Uhrig Melanie Boxberg Katja Steiger Julia Slotta-Huspenina Sebastian Ochsenreither Nikolas von Bubnoff Sebastian Bauer Melanie Boerries Philipp J Jost Kristina Schenck Iska Dresing Florian Bassermann Helmut Friess Daniel Reim Konrad Grützmann Katrin Pfütze Barbara Klink Evelin Schröck Bernhard Haller Bernhard Kuster Matthias Mann Wilko Weichert Stefan Fröhling Roland Rad Michael Hiltensperger Angela M Krackhardt German Cancer Consortium (DKTK) partner site Munich and German Cancer Research Center (DKFZ) Heidelberg Germany. Technical University of Munich TUM School of Medicine Klinikum rechts der Isar IIIrd Medical Department Munich Germany. Technical University of Munich TUM School of Medicine Klinikum rechts der Isar IInd Medical Department Munich Germany. Technical University of Munich TUM School of Medicine Center for Translational Cancer Research (TranslaTUM) Munich Germany. Technical University of Munich TUM School of Medicine Institute of Molecular Oncology and Functional Genomics Munich Germany. Department of Proteomics and Signal Transduction Max Plank Institute of Biochemistry Munich Germany. Institute for Research in Biomedicine Università della Svizzera italiana Bellinzona Switzerland. Technical University of Munich TUM School of Life Sciences Chair of Proteomics and Bioanalytics Freising Germany. Technical University of Munich TUM School of Life Sciences Computational Mass Spectrometry Freising Germany. German Cancer Consortium (DKTK) partner site Heidelberg and German Cancer Research Center (DKFZ) Heidelberg Germany. Molecular Precision Oncology Program NCT Heidelberg Heidelberg Germany. Technical University of Munich TUM School of Medicine Klinikum rechts der Isar Institute of Pathology Munich Germany. German Cancer Consortium (DKTK) partner site Berlin and German Cancer Research Center (DKFZ) Heidelberg Germany. Charité Comprehensive Cancer Center Charité - Universitätsmedizin Berlin Berlin Germany. Department of Hematology Oncology and Tumor Immunology Charité - Universitätsmedizin Berlin Berlin Germany. German Cancer Consortium (DKTK) partner site Freiburg and German Cancer Research Center (DKFZ) Heidelberg Germany. Institute of Medical Bioinformatics and Systems Medicine (IBSM) Medical Center - University of Freiburg Faculty of Medicine University of Freiburg Freiburg Germany. Department of Hematology and Oncology Medical Center Universit

来源：评论

学校读者我要写书评

暂无评论

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

引用

Gynecologic oncology 2019年第2期153卷 343-355页

作者： Kate Lawrenson Fengju Song Dennis J Hazelett Siddhartha P Kar Jonathan Tyrer Catherine M Phelan Rosario I Corona Norma I Rodríguez-Malavé Ji-Hei Seo Emily Adler Simon G Coetzee Felipe Segato Marcos A S Fonseca Christopher I Amos Michael E Carney Georgia Chenevix-Trench Jiyeob Choi Jennifer A Doherty Weihua Jia Gang J Jin Byoung-Gie Kim Nhu D Le Juyeon Lee Lian Li Boon K Lim Noor A Adenan Mika Mizuno Boyoung Park Celeste L Pearce Kang Shan Yongyong Shi Xiao-Ou Shu Weiva Sieh Pamela J Thompson Lynne R Wilkens Qingyi Wei Yin L Woo Li Yan Beth Y Karlan Matthew L Freedman Houtan Noushmehr Ellen L Goode Andrew Berchuck Thomas A Sellers Soo-Hwang Teo Wei Zheng Keitaro Matsuo Sue Park Kexin Chen Paul D P Pharoah Simon A Gayther Marc T Goodman Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Center 8700 Beverly Boulevard Suite 290W Los Angeles CA USA Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Electronic address: kate.lawrenson@***. National Clinical Research Center for Cancer Tianjin Medical University Cancer Institute and Hospital Tianjin China Department of Epidemiology and Biostatistics Key Laboratory of Cancer Prevention and Therapy Tianjin China. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Oncology Centre for Cancer Genetic Epidemiology University of Cambridge Strangeways Research Laboratory Cambridge UK. Department of Gynecologic Oncology Moffitt Cancer Center Tampa FL USA Department of Cancer Epidemiology Moffitt Cancer Center Tampa FL USA. Center for Bioinformatics and Functional Genomics Cedars Sinai Genomics Core Cedars-Sinai Medical Center Los Angeles CA USA. Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA. Department of Preventive Medicine University of Southern California Keck School of Medicine 1450 Biggy Street Los Angeles CA USA. Department of Genetics Ribeirão Preto Medical School University of São Paulo 14049-900 Brazil. Institute for Clinical and Translational Research Department of Medicine Baylor School of Medicine HoustonTX USA. Department of Obstetrics and Gynecology John A. Burns School of Medicine University of Hawaii Honolulu HI USA. Genetics and Computational Biology Department QIMR Berghofer Medical Research Institute 300 Herston Road Herston QLD 4006 Australia. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea Cancer Research Institute Seoul National University Seoul Republic of Korea Department of Biomedical Science Graduate School Seoul National Un

OBJECTIVE:Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS:Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS:At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10). SNP rs6902488 at 6p25.2 (r = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10). CONCLUSION:While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

关键词： Asian ancestry Enhancer Epithelial ovarian cancer Gene regulation Genome-wide association study eQTL

来源：评论

学校读者我要写书评

暂无评论

Quantum computing at the frontiers of biological sciences

arXiv

引用

arXiv 2019年

作者： Emani, Prashant S. Warrell, Jonathan Anticevic, Alan Bekiranov, Stefan Gandal, Michael McConnell, Michael J. Sapiro, Guillermo Aspuru-Guzik, Alán Baker, Justin Bastiani, Matteo McClure, Patrick Murray, John Sotiropoulos, Stamatios N. Taylor, Jacob Senthil, Geetha Lehner, Thomas Gerstein, Mark B. Harrow, Aram W. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Yale School of Medicine Department of Psychiatry New HavenCT06511 United States University of Virginia School of Medicine Department of Biochemistry and Molecular Genetics CharlottesvilleVA22903 United States Department of Psychiatry Semel Institute David Geffen School of Medicine University of California–Los Angeles 695 Charles E. Young Drive South Los AngelesCA90095 United States Univ. of Virginia School of Medicine Department of Neuroscience CharlottesvilleVA22903 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Chemistry University of Toronto 80 St. George Street TorontoONM5S 3H6 Canada TorontoONM5S 1M1 Canada CIFAR Artificial Intelligence Research Chair Vector Institute TorontoONM5S 1M1 Canada Department of Computer Science University of Toronto 40 St. George Street TorontoONM5S 2E4 Canada Schizophrenia and Bipolar Disorder Program McLean Hospital BelmontMA02478 United States Department of Psychiatry Harvard Medical School BostonMA02114 United States Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham NottinghamNG7 2RD United Kingdom Machine Learning Team National Institute of Mental Health BethesdaMD20892 United States Section on Functional Imaging Methods National Institute of Mental Health BethesdaMD20892 United States Department of Psychiatry Yale University School of Medicine New HavenCT06511 United States Department of Physics Yale University New HavenCT06511 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States National Institute of Standards and Technology GaithersburgMD20899 United States Office of Genomics Research Coordination N

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study

引用

Translational psychiatry 2024年第1期14卷 109页

作者： Anna H Ou Sara B Rosenthal Mazda Adli Kazufumi Akiyama Nirmala Akula Martin Alda Azmeraw T Amare Raffaella Ardau Bárbara Arias Jean-Michel Aubry Lena Backlund Michael Bauer Bernhard T Baune Frank Bellivier Antonio Benabarre Susanne Bengesser Abesh Kumar Bhattacharjee Joanna M Biernacka Pablo Cervantes Guo-Bo Chen Hsi-Chung Chen Caterina Chillotti Sven Cichon Scott R Clark Francesc Colom David A Cousins Cristiana Cruceanu Piotr M Czerski Clarissa R Dantas Alexandre Dayer Maria Del Zompo Franziska Degenhardt J Raymond DePaulo Bruno Étain Peter Falkai Frederike Tabea Fellendorf Ewa Ferensztajn-Rochowiak Andreas J Forstner Louise Frisén Mark A Frye Janice M Fullerton Sébastien Gard Julie S Garnham Fernando S Goes Maria Grigoroiu-Serbanescu Paul Grof Oliver Gruber Ryota Hashimoto Joanna Hauser Urs Heilbronner Stefan Herms Per Hoffmann Andrea Hofmann Liping Hou Stephane Jamain Esther Jiménez Jean-Pierre Kahn Layla Kassem Tadafumi Kato Sarah Kittel-Schneider Barbara König Po-Hsiu Kuo Ichiro Kusumi Nina Lackner Gonzalo Laje Mikael Landén Catharina Lavebratt Marion Leboyer Susan G Leckband Carlos A López Jaramillo Glenda MacQueen Mario Maj Mirko Manchia Cynthia Marie-Claire Lina Martinsson Manuel Mattheisen Michael J McCarthy Susan L McElroy Francis J McMahon Philip B Mitchell Marina Mitjans Francis M Mondimore Palmiero Monteleone Caroline M Nievergelt Markus M Nöthen Tomas Novák Urban Ösby Norio Ozaki Sergi Papiol Roy H Perlis Claudia Pisanu James B Potash Andrea Pfennig Daniela Reich-Erkelenz Andreas Reif Eva Z Reininghaus Marcella Rietschel Guy A Rouleau Janusz K Rybakowski Martin Schalling Peter R Schofield K Oliver Schubert Thomas G Schulze Barbara W Schweizer Florian Seemüller Giovanni Severino Tatyana Shekhtman Paul D Shilling Kazutaka Shimoda Christian Simhandl Claire M Slaney Alessio Squassina Thomas Stamm Pavla Stopkova Sarah K Tighe Alfonso Tortorella Gustavo Turecki Eduard Vieta Julia Volkert Stephanie Witt Naomi R Wray Adam Wright L Trevor Young Peter P Zandi John R Kelsoe Department of Psychiatry University of California San Diego La Jolla CA USA. Center for Computational Biology and Bioinformatics Department of Medicine University of California San Diego La Jolla CA USA. Department of Psychiatry and Psychotherapy Charité- Universitätsmedizin Berlin Campus Charité Mitte Berlin Germany. Fliedner Klinik Berlin Center for Psychiatry Psychotherapy and Psychosomatic Medicine Berlin Germany. Department of Biological Psychiatry and Neuroscience Dokkyo Medical University School of Medicine Mibu Japan. Intramural Research Program National Institute of Mental Health National Institutes of Health US Department of Health & Human Services Bethesda MD USA. Department of Psychiatry Dalhousie University Halifax NS Canada. National Institute of Mental Health Klecany Czech Republic. Discipline of Psychiatry University of Adelaide Adelaide SA Australia. Unit of Clinical Pharmacology Hospital University Agency of Cagliari Cagliari Italy. Department of Evolutive Biology Ecology and Environmental Sciences Facultat de Biologia and Institut de Biomedicina (IBUB) Universitat de Barcelona Barcelona Spain. CIBER de Salud Mental ISCIII Madrid Barcelona Catalonia Spain. Department of Mental Health and Psychiatry Mood Disorders Unit-Geneva University Hospitals Geneva Switzerland. Department of Molecular Medicine and Surgery Karolinska Institutet and Center for Molecular Medicine Karolinska University Hospital Stockholm Sweden. Department of Psychiatry and Psychotherapy University Hospital Carl Gustav Carus Medical Faculty Technische Universität Dresden Dresden Germany. Department of Psychiatry University of Münster Münster Germany. INSERM UMR-S 1144-Université Paris Cité Département de Psychiatrie et de Médecine Addictologique AP-HP Groupe Hospitalier Lariboisière-F Widal Paris France. Bipolar and Depressive Disorders Unit Institute of Neuroscience Hospital Clinic University of Barcelona IDIBAPS CIBERSAM ISCIII Barcelona Catalonia Spa

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：