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The Vocaloids~!
ALL THE VOCALOIDS~! BY D J DATE MASAMUNE NEED TO KNOWS • Panel will be available online + list of all my resources – Will upload .pdf of PowerPoint that will be available post-con • Contact info. – Blog: djdatemasamune.wordpress.com • Especially if you have ANY feedback • Even if you leave mid-way, feel free to get one before you go • If you have any questions left, feel free to ask me after the panel or e-mail me DISCLAIMERS • Can only show so many Vocaloids – & which songs to show from each – Not even going to talk about costumes • B/c determining what’s popular/obscure btwn. Japanese/American culture can be difficult, sorry if you’re super familiar w/ any Vocaloid mentioned ^.^; – Based ‘popular’ ones off what I see (official) merch for the most (& even then) • Additionally, will ask lvl of familiarity w/ every Vocaloid • Every iteration of this panel plan to feature/swap out different Vocaloids • Only going over Vocaloids, not the history of the software, appends, etc. • Format of panel… POPULAR ONES VOCALOIDS YUKARI YUZUKI AOKI LAPIS MERLI CALNE CA (骸音シーエ Karune Shii-e) DAINA DEX Sharkie P VY1 VY2 ANON & KANON FUKASE UTATANE PIKO YOWANE HAKU TETO KASANE ARSLOID HIYAMA KIYOTERU KAAI YUKI LILY YOHIOloid V FLOWER Name: Don’t Say Lazy Lyrics: Sachiko Omori Composition: Hiroyuki Maezawa SeeU MAIKA GALACO QUESTIONS? BEFORE YOU GO… • Help yourself to my business cards If you have any questions, comments, feedback, etc., contact me however – My blog, e-mail, comment on a relating blog post, smoke signals, carrier pigeons, whatever tickles -
Improving the Prediction of Transcription Factor Binding Sites To
Improving the prediction of transcription factor binding sites to aid the interpretation of non-coding single nucleotide variants. Narayan Jayaram Research Department of Structural and Molecular Biology University College London A thesis submitted to University College London for the degree of Doctor of Philosophy 1 Declaration I, Narayan Jayaram confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Narayan Jayaram 2 Abstract Single nucleotide variants (SNVs) that occur in transcription factor binding sites (TFBSs) can disrupt the binding of transcription factors and alter gene expression which can cause inherited diseases and act as driver SNVs in cancer. The identification of SNVs in TFBSs has historically been challenging given the limited number of experimentally characterised TFBSs. The recent ENCODE project has resulted in the availability of ChIP-Seq data that provides genome wide sets of regions bound by transcription factors. These data have the potential to improve the identification of SNVs in TFBSs. However, as the ChIP-Seq data identify a broader range of DNA in which a transcription factor binds, computational prediction is required to identify the precise TFBS. Prediction of TFBSs involves scanning a DNA sequence with a Position Weight Matrix (PWM) using a pattern matching tool. This thesis focusses on the prediction of TFBSs by: (a) evaluating a set of locally-installable pattern-matching tools and identifying the best performing tool (FIMO), (b) using the ENCODE ChIP-Seq data to evaluate a set of de novo motif discovery tools that are used to derive PWMs which can handle large volumes of data, (c) identifying the best performing tool (rGADEM), (d) using rGADEM to generate a set of PWMs from the ENCODE ChIP-Seq data and (e) by finally checking that the selection of the best pattern matching tool is not unduly influenced by the choice of PWMs. -
Applied Category Theory for Genomics – an Initiative
Applied Category Theory for Genomics { An Initiative Yanying Wu1,2 1Centre for Neural Circuits and Behaviour, University of Oxford, UK 2Department of Physiology, Anatomy and Genetics, University of Oxford, UK 06 Sept, 2020 Abstract The ultimate secret of all lives on earth is hidden in their genomes { a totality of DNA sequences. We currently know the whole genome sequence of many organisms, while our understanding of the genome architecture on a systematic level remains rudimentary. Applied category theory opens a promising way to integrate the humongous amount of heterogeneous informations in genomics, to advance our knowledge regarding genome organization, and to provide us with a deep and holistic view of our own genomes. In this work we explain why applied category theory carries such a hope, and we move on to show how it could actually do so, albeit in baby steps. The manuscript intends to be readable to both mathematicians and biologists, therefore no prior knowledge is required from either side. arXiv:2009.02822v1 [q-bio.GN] 6 Sep 2020 1 Introduction DNA, the genetic material of all living beings on this planet, holds the secret of life. The complete set of DNA sequences in an organism constitutes its genome { the blueprint and instruction manual of that organism, be it a human or fly [1]. Therefore, genomics, which studies the contents and meaning of genomes, has been standing in the central stage of scientific research since its birth. The twentieth century witnessed three milestones of genomics research [1]. It began with the discovery of Mendel's laws of inheritance [2], sparked a climax in the middle with the reveal of DNA double helix structure [3], and ended with the accomplishment of a first draft of complete human genome sequences [4]. -
Gene Prediction: the End of the Beginning Comment Colin Semple
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by PubMed Central http://genomebiology.com/2000/1/2/reports/4012.1 Meeting report Gene prediction: the end of the beginning comment Colin Semple Address: Department of Medical Sciences, Molecular Medicine Centre, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK. E-mail: [email protected] Published: 28 July 2000 reviews Genome Biology 2000, 1(2):reports4012.1–4012.3 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2000/1/2/reports/4012 © GenomeBiology.com (Print ISSN 1465-6906; Online ISSN 1465-6914) Reducing genomes to genes reports A report from the conference entitled Genome Based Gene All ab initio gene prediction programs have to balance sensi- Structure Determination, Hinxton, UK, 1-2 June, 2000, tivity against accuracy. It is often only possible to detect all organised by the European Bioinformatics Institute (EBI). the real exons present in a sequence at the expense of detect- ing many false ones. Alternatively, one may accept only pre- dictions scoring above a more stringent threshold but lose The draft sequence of the human genome will become avail- those real exons that have lower scores. The trick is to try and able later this year. For some time now it has been accepted increase accuracy without any large loss of sensitivity; this deposited research that this will mark a beginning rather than an end. A vast can be done by comparing the prediction with additional, amount of work will remain to be done, from detailing independent evidence. -
The EMBL-European Bioinformatics Institute the Hub for Bioinformatics in Europe
The EMBL-European Bioinformatics Institute The hub for bioinformatics in Europe Blaise T.F. Alako, PhD [email protected] www.ebi.ac.uk What is EMBL-EBI? • Part of the European Molecular Biology Laboratory • International, non-profit research institute • Europe’s hub for biological data, services and research The European Molecular Biology Laboratory Heidelberg Hamburg Hinxton, Cambridge Basic research Structural biology Bioinformatics Administration Grenoble Monterotondo, Rome EMBO EMBL staff: 1500 people Structural biology Mouse biology >60 nationalities EMBL member states Austria, Belgium, Croatia, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom Associate member state: Australia Who we are ~500 members of staff ~400 work in services & support >53 nationalities ~120 focus on basic research EMBL-EBI’s mission • Provide freely available data and bioinformatics services to all facets of the scientific community in ways that promote scientific progress • Contribute to the advancement of biology through basic investigator-driven research in bioinformatics • Provide advanced bioinformatics training to scientists at all levels, from PhD students to independent investigators • Help disseminate cutting-edge technologies to industry • Coordinate biological data provision throughout Europe Services Data and tools for molecular life science www.ebi.ac.uk/services Browse our services 9 What services do we provide? Labs around the -
Functional Effects Detailed Research Plan
GeCIP Detailed Research Plan Form Background The Genomics England Clinical Interpretation Partnership (GeCIP) brings together researchers, clinicians and trainees from both academia and the NHS to analyse, refine and make new discoveries from the data from the 100,000 Genomes Project. The aims of the partnerships are: 1. To optimise: • clinical data and sample collection • clinical reporting • data validation and interpretation. 2. To improve understanding of the implications of genomic findings and improve the accuracy and reliability of information fed back to patients. To add to knowledge of the genetic basis of disease. 3. To provide a sustainable thriving training environment. The initial wave of GeCIP domains was announced in June 2015 following a first round of applications in January 2015. On the 18th June 2015 we invited the inaugurated GeCIP domains to develop more detailed research plans working closely with Genomics England. These will be used to ensure that the plans are complimentary and add real value across the GeCIP portfolio and address the aims and objectives of the 100,000 Genomes Project. They will be shared with the MRC, Wellcome Trust, NIHR and Cancer Research UK as existing members of the GeCIP Board to give advance warning and manage funding requests to maximise the funds available to each domain. However, formal applications will then be required to be submitted to individual funders. They will allow Genomics England to plan shared core analyses and the required research and computing infrastructure to support the proposed research. They will also form the basis of assessment by the Project’s Access Review Committee, to permit access to data. -
Algorithms for Computational Biology 8Th International Conference, Alcob 2021 Missoula, MT, USA, June 7–11, 2021 Proceedings
Lecture Notes in Bioinformatics 12715 Subseries of Lecture Notes in Computer Science Series Editors Sorin Istrail Brown University, Providence, RI, USA Pavel Pevzner University of California, San Diego, CA, USA Michael Waterman University of Southern California, Los Angeles, CA, USA Editorial Board Members Søren Brunak Technical University of Denmark, Kongens Lyngby, Denmark Mikhail S. Gelfand IITP, Research and Training Center on Bioinformatics, Moscow, Russia Thomas Lengauer Max Planck Institute for Informatics, Saarbrücken, Germany Satoru Miyano University of Tokyo, Tokyo, Japan Eugene Myers Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Marie-France Sagot Université Lyon 1, Villeurbanne, France David Sankoff University of Ottawa, Ottawa, Canada Ron Shamir Tel Aviv University, Ramat Aviv, Tel Aviv, Israel Terry Speed Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia Martin Vingron Max Planck Institute for Molecular Genetics, Berlin, Germany W. Eric Wong University of Texas at Dallas, Richardson, TX, USA More information about this subseries at http://www.springer.com/series/5381 Carlos Martín-Vide • Miguel A. Vega-Rodríguez • Travis Wheeler (Eds.) Algorithms for Computational Biology 8th International Conference, AlCoB 2021 Missoula, MT, USA, June 7–11, 2021 Proceedings 123 Editors Carlos Martín-Vide Miguel A. Vega-Rodríguez Rovira i Virgili University University of Extremadura Tarragona, Spain Cáceres, Spain Travis Wheeler University of Montana Missoula, MT, USA ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Bioinformatics ISBN 978-3-030-74431-1 ISBN 978-3-030-74432-8 (eBook) https://doi.org/10.1007/978-3-030-74432-8 LNCS Sublibrary: SL8 – Bioinformatics © Springer Nature Switzerland AG 2021 This work is subject to copyright. -
Computational Pan-Genomics: Status, Promises and Challenges
bioRxiv preprint doi: https://doi.org/10.1101/043430; this version posted March 12, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Computational Pan-Genomics: Status, Promises and Challenges Tobias Marschall1,2, Manja Marz3,60,61,62, Thomas Abeel49, Louis Dijkstra6,7, Bas E. Dutilh8,9,10, Ali Ghaffaari1,2, Paul Kersey11, Wigard P. Kloosterman12, Veli M¨akinen13, Adam Novak15, Benedict Paten15, David Porubsky16, Eric Rivals17,63, Can Alkan18, Jasmijn Baaijens5, Paul I. W. De Bakker12, Valentina Boeva19,64,65,66, Francesca Chiaromonte20, Rayan Chikhi21, Francesca D. Ciccarelli22, Robin Cijvat23, Erwin Datema24,25,26, Cornelia M. Van Duijn27, Evan E. Eichler28, Corinna Ernst29, Eleazar Eskin30,31, Erik Garrison32, Mohammed El-Kebir5,33,34, Gunnar W. Klau5, Jan O. Korbel11,35, Eric-Wubbo Lameijer36, Benjamin Langmead37, Marcel Martin59, Paul Medvedev38,39,40, John C. Mu41, Pieter Neerincx36, Klaasjan Ouwens42,67, Pierre Peterlongo43, Nadia Pisanti44,45, Sven Rahmann29, Ben Raphael46,47, Knut Reinert48, Dick de Ridder50, Jeroen de Ridder49, Matthias Schlesner51, Ole Schulz-Trieglaff52, Ashley Sanders53, Siavash Sheikhizadeh50, Carl Shneider54, Sandra Smit50, Daniel Valenzuela13, Jiayin Wang70,71,72, Lodewyk Wessels56, Ying Zhang23,5, Victor Guryev16,12, Fabio Vandin57,34, Kai Ye68,69,72 and Alexander Sch¨onhuth5 1Center for Bioinformatics, Saarland University, Saarbr¨ucken, Germany; 2Max Planck Institute for Informatics, Saarbr¨ucken, -
Diversity Data Report 2019 Diversity Data Report 2019 Issued: November 2020 DES6507
Diversity data report 2019 Diversity data report 2019 Issued: November 2020 DES6507 The text of this work is licensed under the terms of the Creative Commons Attribution License which permits unrestricted use, provided the original author and source are credited. The license is available at: creativecommons.org/licenses/by/4.0 Images are not covered by this license. This report can be viewed online at: royalsociety.org/diversity Contents Introduction .....................................................4 The Fellowship ..................................................11 Committees, panels and working groups ..........................19 Research Fellowship Grants ......................................26 Scientific programmes ...........................................38 Public engagement .............................................50 Publishing ......................................................62 Schools engagement ............................................67 Royal Society staff ..............................................72 Gender pay gap .................................................75 Definitions .....................................................77 DIVERSITY DATA REPORT 2019 3 Introduction The Royal Society is a Fellowship of many of the world’s most eminent scientists and is the oldest scientific academy in continuous existence. The Society is committed to increasing sections of this report such as organisers, diversity in science, technology, engineering chairs and speakers at scientific meetings, and mathematics (‘STEM’) -
UNIVERSITY of CALIFORNIA SAN DIEGO Making Sense of Microbial
UNIVERSITY OF CALIFORNIA SAN DIEGO Making sense of microbial populations from representative samples A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by James T. Morton Committee in charge: Professor Rob Knight, Chair Professor Pieter Dorrestein Professor Rachel Dutton Professor Yoav Freund Professor Siavash Mirarab 2018 Copyright James T. Morton, 2018 All rights reserved. The dissertation of James T. Morton is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California San Diego 2018 iii DEDICATION To my friends and family who paved the road and lit the journey. iv EPIGRAPH The ‘paradox’ is only a conflict between reality and your feeling of what reality ‘ought to be’ —Richard Feynman v TABLE OF CONTENTS Signature Page . iii Dedication . iv Epigraph . .v Table of Contents . vi List of Abbreviations . ix List of Figures . .x List of Tables . xi Acknowledgements . xii Vita ............................................. xiv Abstract of the Dissertation . xvii Chapter 1 Methods for phylogenetic analysis of microbiome data . .1 1.1 Introduction . .2 1.2 Phylogenetic Inference . .4 1.3 Phylogenetic Comparative Methods . .6 1.4 Ancestral State Reconstruction . .9 1.5 Analysis of phylogenetic variables . 11 1.6 Using Phylogeny-Aware Distances . 15 1.7 Challenges of phylogenetic analysis . 18 1.8 Discussion . 19 1.9 Acknowledgements . 21 Chapter 2 Uncovering the horseshoe effect in microbial analyses . 23 2.1 Introduction . 24 2.2 Materials and Methods . 34 2.3 Acknowledgements . 35 Chapter 3 Balance trees reveal microbial niche differentiation . 36 3.1 Introduction . -
Curriculum Vitae – Prof. Anders Krogh Personal Information
Curriculum Vitae – Prof. Anders Krogh Personal Information Date of Birth: May 2nd, 1959 Private Address: Borgmester Jensens Alle 22, st th, 2100 København Ø, Denmark Contact information: Dept. of Biology, Univ. of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen, Denmark. +45 3532 1329, [email protected] Web: https://scholar.google.com/citations?user=-vGMjmwAAAAJ Education Sept 1991 Ph.D. (Physics), Niels Bohr Institute, Univ. of Copenhagen, Denmark June 1987 Cand. Scient. [M. Sc.] (Physics and mathematics), NBI, Univ. of Copenhagen Professional / Work Experience (since 2000) 2018 – Professor of Bionformatics, Dept of Computer Science (50%) and Dept of Biology (50%), Univ. of Copenhagen 2002 – 2018 Professor of Bionformatics, Dept of Biology, Univ. of Copenhagen 2009 – 2018 Head of Section for Computational and RNA Biology, Dept. of Biology, Univ. of Copenhagen 2000–2002 Associate Prof., Technical Univ. of Denmark (DTU), Copenhagen Prices and Awards 2017 – Fellow of the International Society for Computational Biology https://www.iscb.org/iscb- fellows-program 2008 – Fellow, Royal Danish Academy of Sciences and Letters Public Activities & Appointments (since 2009) 2014 – Board member, Elixir, European Infrastructure for Life Science. 2014 – Steering committee member, Danish Elixir Node. 2012 – 2016 Board member, Bioinformatics Infrastructure for Life Sciences (BILS), Swedish Research Council 2011 – 2016 Director, Centre for Computational and Applied Transcriptomics (COAT) 2009 – Associate editor, BMC Bioinformatics Publications § Google Scholar: https://scholar.google.com/citations?user=-vGMjmwAAAAJ § ORCID: 0000-0002-5147-6282. ResearcherID: M-1541-2014 § Co-author of 130 peer-reviewed papers and 2 monographs § 63,000 citations and h-index of 74 (Google Scholar, June 2019) § H-index of 54 in Web of science (June 2019) § Publications in high-impact journals: Nature (5), Science (1), Cell (1), Nature Genetics (2), Nature Biotechnology (2), Nature Communications (4), Cell (1, to appear), Genome Res. -
A Multiscale Tool to Explore Genomic Conservation
SynVisio: A Multiscale Tool to Explore Genomic Conservation A Thesis Submitted to the College of Graduate and Postdoctoral Studies in Partial Fulfillment of the Requirements for the degree of Master of Science in the Department of Computer Science University of Saskatchewan Saskatoon By Venkat Kiran Bandi ©Venkat Kiran Bandi, May/2020. All rights reserved. Permission to Use In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree from the University of Saskatchewan, I agree that the Libraries of this University may make it freely available for inspection. I further agree that permission for copying of this thesis in any manner, in whole or in part, for scholarly purposes may be granted by the professor or professors who supervised my thesis work or, in their absence, by the Head of the Department or the Dean of the College in which my thesis work was done. It is understood that any copying or publication or use of this thesis or parts thereof for financial gain shall not be allowed without my written permission. It is also understood that due recognition shall be given to me and to the University of Saskatchewan in any scholarly use which may be made of any material in my thesis. Requests for permission to copy or to make other use of material in this thesis in whole or part should be addressed to: Head of the Department of Computer Science 176 Thorvaldson Building 110 Science Place University of Saskatchewan Saskatoon, Saskatchewan Canada S7N 5C9 Or Dean College of Graduate and Postdoctoral Studies University of Saskatchewan 116 Thorvaldson Building, 110 Science Place Saskatoon, Saskatchewan S7N 5C9 Canada i Abstract Comparative analysis of genomes is an important area in biological research that can shed light on an organism's internal functions and evolutionary history.