Lighting the Way for Researchers Everywhere
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
• La Gestion Efficace De L’Énergie • Le Réseautage Planétaire • Les Processus Géophysiques • L’Économie Globale, La Sécurité Et La Stabilité
SupérieureS atiqueS athéM e M inaire D SéM The planet on which we live and the challenges that we face on this planet become increasingly complex as ecological, economic and social systems are large intertwined networks governed by dynamic processes and feedback loops. Mathematical models are indispensable in understanding and managing such systems since they provide insight into governing processes; they help predict future behavior; and they allow for risk-free evaluation of possible interventions. The goal of this thematic program is to tackle pressing and emerging challenges in population and ecosystem health, including understanding and controlling major transmissible diseases, optimizing and monitoring vaccination, predicting the impacts of climate change on invasive species, protecting biodiversity and managing ecosystems sustainably. This pan-Canadian program will bring together the international community of researchers who work on these topics in a series of workshops to foster exchange and stimulate cross-disciplinary research between all scientific areas involved, to discuss perspectives and directions for future advances in the field, including new models and methods and to foster tighter links between the research community, government agencies and policy makers. Three summer schools will introduce graduate students and postdoctoral fellows to the art of modeling living systems and to the latest tools and techniques to analyze these models. SCIENTIFIC COMMITTEE Jacques Bélair Mark Lewis (Montréal) Models and Methods in Ecology (Alberta) Frithjof Lutscher and Epidemiology Mathematical Modeling James Watmough (Ottawa) February 6-8, 2013 (UNB) of Indigenous Population Jianhong Wu CRM, Montréal (York) Organizers: Jacques Bélair (Montréal), Health Jianhong Wu (York) September 28-29, 2013 AISENSTADT CHAIRS BIRS Bryan Grenfell (Princeton), May 2013 Graphic Design: www.neograf.ca Simon A. -
The Principled Design of Large-Scale Recursive Neural Network Architectures–DAG-Rnns and the Protein Structure Prediction Problem
Journal of Machine Learning Research 4 (2003) 575-602 Submitted 2/02; Revised 4/03; Published 9/03 The Principled Design of Large-Scale Recursive Neural Network Architectures–DAG-RNNs and the Protein Structure Prediction Problem Pierre Baldi [email protected] Gianluca Pollastri [email protected] School of Information and Computer Science Institute for Genomics and Bioinformatics University of California, Irvine Irvine, CA 92697-3425, USA Editor: Michael I. Jordan Abstract We describe a general methodology for the design of large-scale recursive neural network architec- tures (DAG-RNNs) which comprises three fundamental steps: (1) representation of a given domain using suitable directed acyclic graphs (DAGs) to connect visible and hidden node variables; (2) parameterization of the relationship between each variable and its parent variables by feedforward neural networks; and (3) application of weight-sharing within appropriate subsets of DAG connec- tions to capture stationarity and control model complexity. Here we use these principles to derive several specific classes of DAG-RNN architectures based on lattices, trees, and other structured graphs. These architectures can process a wide range of data structures with variable sizes and dimensions. While the overall resulting models remain probabilistic, the internal deterministic dy- namics allows efficient propagation of information, as well as training by gradient descent, in order to tackle large-scale problems. These methods are used here to derive state-of-the-art predictors for protein structural features such as secondary structure (1D) and both fine- and coarse-grained contact maps (2D). Extensions, relationships to graphical models, and implications for the design of neural architectures are briefly discussed. -
Methodology for Predicting Semantic Annotations of Protein Sequences by Feature Extraction Derived of Statistical Contact Potentials and Continuous Wavelet Transform
Universidad Nacional de Colombia Sede Manizales Master’s Thesis Methodology for predicting semantic annotations of protein sequences by feature extraction derived of statistical contact potentials and continuous wavelet transform Author: Supervisor: Gustavo Alonso Arango Dr. Cesar German Argoty Castellanos Dominguez A thesis submitted in fulfillment of the requirements for the degree of Master’s on Engineering - Industrial Automation in the Department of Electronic, Electric Engineering and Computation Signal Processing and Recognition Group June 2014 Universidad Nacional de Colombia Sede Manizales Tesis de Maestr´ıa Metodolog´ıapara predecir la anotaci´on sem´antica de prote´ınaspor medio de extracci´on de caracter´ısticas derivadas de potenciales de contacto y transformada wavelet continua Autor: Tutor: Gustavo Alonso Arango Dr. Cesar German Argoty Castellanos Dominguez Tesis presentada en cumplimiento a los requerimientos necesarios para obtener el grado de Maestr´ıaen Ingenier´ıaen Automatizaci´onIndustrial en el Departamento de Ingenier´ıaEl´ectrica,Electr´onicay Computaci´on Grupo de Procesamiento Digital de Senales Enero 2014 UNIVERSIDAD NACIONAL DE COLOMBIA Abstract Faculty of Engineering and Architecture Department of Electronic, Electric Engineering and Computation Master’s on Engineering - Industrial Automation Methodology for predicting semantic annotations of protein sequences by feature extraction derived of statistical contact potentials and continuous wavelet transform by Gustavo Alonso Arango Argoty In this thesis, a method to predict semantic annotations of the proteins from its primary structure is proposed. The main contribution of this thesis lies in the implementation of a novel protein feature representation, which makes use of the pairwise statistical contact potentials describing the protein interactions and geometry at the atomic level. -
BIOGRAPHICAL SKETCH NAME: Berger
BIOGRAPHICAL SKETCH NAME: Berger, Bonnie eRA COMMONS USER NAME (credential, e.g., agency login): BABERGER POSITION TITLE: Simons Professor of Mathematics and Professor of Electrical Engineering and Computer Science EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.) EDUCATION/TRAINING DEGREE Completion (if Date FIELD OF STUDY INSTITUTION AND LOCATION applicable) MM/YYYY Brandeis University, Waltham, MA AB 06/1983 Computer Science Massachusetts Institute of Technology SM 01/1986 Computer Science Massachusetts Institute of Technology Ph.D. 06/1990 Computer Science Massachusetts Institute of Technology Postdoc 06/1992 Applied Mathematics A. Personal Statement Advances in modern biology revolve around automated data collection and sharing of the large resulting datasets. I am considered a pioneer in the area of bringing computer algorithms to the study of biological data, and a founder in this community that I have witnessed grow so profoundly over the last 26 years. I have made major contributions to many areas of computational biology and biomedicine, largely, though not exclusively through algorithmic innovations, as demonstrated by nearly twenty thousand citations to my scientific papers and widely-used software. In recognition of my success, I have just been elected to the National Academy of Sciences and in 2019 received the ISCB Senior Scientist Award, the pinnacle award in computational biology. My research group works on diverse challenges, including Computational Genomics, High-throughput Technology Analysis and Design, Biological Networks, Structural Bioinformatics, Population Genetics and Biomedical Privacy. I spearheaded research on analyzing large and complex biological data sets through topological and machine learning approaches; e.g. -
Fall 2016 Is Available in the Laboratory of Dr
RNA Society Newsletter Aug 2016 From the Desk of the President, Sarah Woodson Greetings to all! I always enjoy attending the annual meetings of the RNA Society, but this year’s meeting in Kyoto was a standout in my opinion. This marked the second time that the RNA meeting has been held in Kyoto as a joint meeting with the RNA Society of Japan. (The first time was in 2011). Particular thanks go to the local organizers Mikiko Siomi and Tom Suzuki who took care of many logistical details, and to all of the organizers, Mikiko, Tom, Utz Fischer, Wendy Gilbert, David Lilley and Erik Sontheimer, for putting together a truly exciting and stimulating scientific program. Of course, the real excitement in the annual RNA meetings comes from all of you who give the talks and present the posters. I always enjoy meeting old friends and colleagues, but the many new participants in this year’s meeting particularly encouraged me. (Continued on p2) In this issue : Desk of the President, Sarah Woodson 1 Highlights of RNA 2016 : Kyoto Japan 4 Annual Society Award Winners 4 Jr Scientist activities 9 Mentor Mentee Lunch 10 New initiatives 12 Desk of our CEO, James McSwiggen 15 New Volunteer Opportunities 16 Chair, Meetings Committee, Benoit Chabot 17 Desk of the Membership Chair, Kristian Baker 18 Thank you Volunteers! 20 Meeting Reports: RNA Sponsored Meetings 22 Upcoming Meetings of Interest 27 Employment 31 1 Although the graceful city of Kyoto and its cultural months. First, in May 2016, the RNA journal treasures beckoned from just beyond the convention instituted a uniform price for manuscript publication hall, the meeting itself held more than enough (see p 12) that simplifies the calculation of author excitement to keep ones attention! Both the quality fees and facilitates the use of color figures to and the “polish” of the scientific presentations were convey scientific information. -
Deep Learning in Chemoinformatics Using Tensor Flow
UC Irvine UC Irvine Electronic Theses and Dissertations Title Deep Learning in Chemoinformatics using Tensor Flow Permalink https://escholarship.org/uc/item/963505w5 Author Jain, Akshay Publication Date 2017 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, IRVINE Deep Learning in Chemoinformatics using Tensor Flow THESIS submitted in partial satisfaction of the requirements for the degree of MASTER OF SCIENCE in Computer Science by Akshay Jain Thesis Committee: Professor Pierre Baldi, Chair Professor Cristina Videira Lopes Professor Eric Mjolsness 2017 c 2017 Akshay Jain DEDICATION To my family and friends. ii TABLE OF CONTENTS Page LIST OF FIGURES v LIST OF TABLES vi ACKNOWLEDGMENTS vii ABSTRACT OF THE THESIS viii 1 Introduction 1 1.1 QSAR Prediction Methods . .2 1.2 Deep Learning . .4 2 Artificial Neural Networks(ANN) 5 2.1 Artificial Neuron . .5 2.2 Activation Function . .7 2.3 Loss function . .8 2.4 Optimization . .8 3 Deep Recursive Architectures 10 3.1 Recurrent Neural Networks (RNN) . 10 3.2 Recursive Neural Networks . 11 3.3 Directed Acyclic Graph Recursive Neural Networks (DAG-RNN) . 11 4 UG-RNN for small molecules 14 4.1 DAG Generation . 16 4.2 Local Information Vector . 16 4.3 Contextual Vectors . 17 4.4 Activity Prediction . 17 4.5 UG-RNN With Contracted Rings (UG-RNN-CR) . 18 4.6 Example: UG-RNN Model of Propionic Acid . 20 5 Implementation 24 6 Data & Results 26 6.1 Aqueous Solubility Prediction . 26 6.2 Melting Point Prediction . 28 iii 7 Conclusions 30 Bibliography 32 A Source Code 37 A.1 UGRNN . -
Mathematical and Computational Biology Graduate Program Bylaws
DRAFT Mathematical and Computational Biology Graduate Program Bylaws January 31, 2005 Drafted by: Vittorio Cristini (Biomedical Engineering) Arthur Lander (Developmental and Cell Biology) Rui (Ray) Luo (Molecular Biology and Biochemistry) Qing Nie (Mathematics) Thorsten Ritz (Physics) Frederic Wan (Mathematics) Other Participants Nancy L. Allbritton (Physiology and Biophysics) Pierre Baldi (Computer Science) Steven P. Gross (Developmental & Cell Biology) John Lowengrub (Mathematics) Eric Mjolsness (Computer Science) Page 1 Table of Contents Section 1. PREAMBLE Section 2. INTRODUCTION AND STATEMENT OF PURPOSE Section 3. DEPARTMENT AND FACULTY PARTICIPATION Section 4. GOVERNANCE 4.1 Executive Committee 4.1.1 Composition 4.1.2 Duties and Responsibilities 4.1.3 Procedures 4.2 The Program Director 4.3 Associate Director 4.4 Committees 4.5 Program Administrator 4.6 Plebiscites 4.7 Program Calendar Section 5. CURRICULUM 5.1 First Year Requirements 5.1.1 Core Courses 5.1.2 Research Laboratory Rotations 5.1.3 Research Seminar Series 5.2 Continuing Training 5.2.1 Selection of a Thesis Advisor and Department 5.2.2 Journal Club Section 6. SUCCESSFUL COMPLETION OF THE PROGRAM Section 7. ADMISSIONS AND STUDENT RECRUITMENT Section 8. ADVISING Page 2 APPENDIX I. Potential Participating Faculty APPENDIX II. Data for Annual Review APPENDIX III. Mathematical and Computational Biology Graduate Programs APPENDIX IV. Additional Educational Information APPENDIX V. NIGMS Funds Complex Biomedical Systems Research Centers APPENDIX VI. NIH and NSF Team Up to Link Math and Biology APPENDIX VII. Examples of Available Funding (Partial Listing) Page 3 SECTION 1. PREAMBLE The biological sciences are entering a new era in which scientific advancement requires a quantitative understanding of large-scale and complex systems. -
Lior Pachter Genome Informatics 2013 Keynote
Stories from the Supplement Lior Pachter! Department of Mathematics and Molecular & Cell Biology! UC Berkeley! ! November 1, 2013! Genome Informatics, CSHL The Cufflinks supplements • C. Trapnell, B.A. Williams, G. Pertea, A. Mortazavi, G. Kwan, M.J. van Baren, S.L. Salzberg, B.J. Wold and L. Pachter, Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation, Nature Biotechnology 28, (2010), p 511–515. Supplementary Material: 42 pages. • C. Trapnell, D.G. Hendrickson, M. Sauvageau, L. Goff, J.L. Rinn and L. Pachter, Differential analysis of gene regulation at transcript resolution with RNA-seq, Nature Biotechnology, 31 (2012), p 46–53. Supplementary Material: 70 pages. A supplementary arithmetic progression? • C. Trapnell, B.A. Williams, G. Pertea, A. Mortazavi, G. Kwan, M.J. van Baren, S.L. Salzberg, B.J. Wold and L. Pachter, Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation, Nature Biotechnology 28, (2010), p 511–515. Supplementary Material: 42 pages. • C. Trapnell, D.G. Hendrickson, M. Sauvageau, L. Goff, J.L. Rinn and L. Pachter, Differential analysis of gene regulation at transcript resolution with RNA- seq, Nature Biotechnology, 31 (2012), p 46–53. Supplementary Material: 70 pages. • A. Roberts and L. Pachter, Streaming algorithms for fragment assignment, Nature Methods 10 (2013), p 71—73. Supplementary Material: 98 pages? The nature methods manuscript checklist The nature methods manuscript checklist Emperor Joseph II: My dear young man, don't take it too hard. Your work is ingenious. It's quality work. And there are simply too many notes, that's all. -
Olga G. Troyanskaya - Sciencewatch.Com
Olga G. Troyanskaya - ScienceWatch.com Home About Scientific Press Room Contact Us ● ScienceWatch Home ● Interviews Featured Interviews Author Commentaries Institutional Interviews 2008 : September 2008 - Author Commentaries : Olga G. Troyanskaya Journal Interviews Podcasts AUTHOR COMMENTARIES - 2008 ● Analyses September 2008 Featured Analyses Olga G. Troyanskaya What's Hot In... Featured Scientist from Essential Science IndicatorsSM Special Topics Dr. Olga Troyanskaya has been named a Rising Star in the field of Computer ● Data & Rankings Science, according to an analysis published by ScienceWatch.com in May. Her citation record in this field in Essential Science Indicators from Thomson Sci-Bytes Reuters includes 31 papers cited a total of 1,533 times between January 1, 1998 and April 30, 2008. She also has Highly Cited Papers in the field of Fast Breaking Papers Clinical Medicine. Dr. Troyanskaya is an Assistant Professor in the New Hot Papers +enlarge Department of Computer Science and the Lewis-Sigler Institute for Integrative Emerging Research Fronts Genomics at Princeton University. Fast Moving Fronts Research Front Maps In the interview below, she talks with us about her highly cited work. Current Classics Top Topics Please tell us a little about your research and educational background. Rising Stars My background is interdisciplinary—I have a Ph.D. in Biomedical Informatics and undergraduate New Entrants degrees in both Computer Science and Biology. My research has always reflected this—I have been involved in bioinformatics research since undergraduate days, first working with Steven Salzberg, then at Country Profiles Johns Hopkins University and The Institute for Genomic Research, and then with Gad Landau and Alex Bolshoy at Haifa University in Israel. -
California State Physician and Surgeon License
Curriculum Vitae MANOJ TIMOTHY ABRAHAM, M.D., F.A.C.S. 845-454-8025 – Office 845-454-8026 – Fax [email protected] www.NYfaceMD.com OFFICE LOCATIONS Facial Plastic, Reconstructive & Laser Surgery / Oasis Medispa 82 North Water Street Poughkeepsie, NY 12601 ENT Faculty Practice 1055 Saw Mill River Road Ardsley, NY 10502 New York Eye & Ear Infirmary 310 East 14th Street New York, NY 10006 EDUCATION UNDERGRADUATE 1989-1993 Bachelor of Science Brown University, Providence, RI Biology with Honors GRADUATE 1993-1997 Doctor of Medicine Cornell University Medical College, New York, NY INTERNSHIP 1997-1998 General Surgery Lenox Hill Hospital, New York, NY RESIDENCY 1998-1999 Otolaryngology Manhattan Eye, Ear & Throat Hospital, New York, NY Head & Neck Surgery 1999-2002 Otolaryngology- New York University Medical Center, New York, NY Head & Neck Surgery FELLOWSHIP 2002-2003 Facial Plastic Surgery University of California, Los Angeles Medical Center and Micro-vascular Los Angeles, California Reconstruction LICENSURE & CERTIFICATION LICENSURE 1997 - New York State Medicine and Surgery License 1997 - Drug Enforcement Agency Registration 2002 - California State Physician and Surgeon License Manoj Timothy Abraham, M.D., F.A.C.S. Curriculum Vitae, July 6, 2018 CERTIFICATION 1997 - National Board of Medical Examiners 2003 - American Board of Otolaryngology – Head & Neck Surgery, MOC expires 2023 2005 - American Board of Facial Plastic and Reconstructive Surgery, MOC expires 2025 APPOINTMENTS & EMPLOYMENT ACADEMIC POSITIONS 2014 – present Attending Faculty, -
Findings, September 2002
INDINGS FNational Institutes of Health September 2002 National Institute of General Medical Sciences inside Baldomero Olivera Secrets of the Killer Snails 2 Elaine Bearer Cells in Motion 8 Edited by Alison Davis under contract 263-MD-20519 Produced by the Office of Communications and Public Liaison National Institute of General Medical Sciences National Institutes of Health On the Cover Photo of Baldomero Olivera: Kerry Matz Photo of Elaine Bearer: John Forasté Editor’s Note Getting together. More than ever, that’s what science is all about. If you think being a scientist means being lonely, you’re wrong! Researchers spend most of their days working with other people. Biomedical scientists at colleges and universities spend up to half of their time teaching some area of biology or chemistry to undergraduate and graduate students. And scientists continually work with students to help turn neat ideas into testable research projects and to sort through the results of an experiment. But biomedical researchers also do a lot of talking to other scientists, and not just biologists. As biology research broadens to include new fields like computer science, physics, and engineering, thinking together about how to attack a problem in an unconventional way can be the most fertile ground for discovery. In assembling the materials for this issue of Findings, the importance of cooperation between scientists became undeniably apparent. Upon asking researchers to review the words about their work, these hard-working women and men insisted on giving credit wherever possible to their students and coworkers—all the people who sit at the benches in their labs and do experiments day in and out. -
Annual Report 2018
ANNUAL REPORT 2017-2018 Table of Contents 2 Director’s Letter 3 History and Mission 4 Faculty 8 Faculty News 12 Faculty Research Programs 22 Scientific Advancements 34 Collaborations 46 Academic and Community Activities 51 Faculty Publications FY 2018 59 Teaching 62 Postdoctoral Trainees 64 Visiting Scientists 65 Graduate Students 69 Grants and Contracts 77 Events 77 Zilkha Seminar Series 80 8th Annual Zach Hall Lecture 82 Los Angeles Brain Bee 84 Soprano and Musical Ambassador Renée Fleming visits Zilkha 85 Music to Remember – LA Opera/Alzheimer’s Greater Los Angeles 86 Searching for Solutions: 5th Annual AD Symposia Held at Zilkha Institute 87 Administration and Operating Budget 88 Development 1 Director’s Letter Dear Friends, The year 2018 began with a strong start when the department of Physiology & Neuroscience was ranked number 3 in the nation according to the Blue Ridge Institute. I am proud of the work we have done to achieve this great honor and in awe of our faculty who have made this accomplishment possible, by receiving a large number of federal awards for their research. Of course, as much as we love to have well-funded research programs, it is the science that really matters, and as you will see across the following pages, we have made great strides in so many different areas, from neural circuits and genomics, to imaging and Alzheimer’s. I am proud of the work we are doing and happy to be recognized for it. In addition to awards received, we welcomed a number of visitors and speakers who came to the Zilkha Neurogenetic Institute, some to share their cutting-edge research, others to learn of the advances we have made.