1 What's So Special About Model Organisms?
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Hyphal Ontogeny in : a Model Organism for All Neurospora Crassa
F1000Research 2016, 5(F1000 Faculty Rev):2801 Last updated: 17 JUL 2019 REVIEW Hyphal ontogeny in Neurospora crassa: a model organism for all seasons [version 1; peer review: 3 approved] Meritxell Riquelme, Leonora Martínez-Núñez Department of Microbiology, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Ensenada, Baja California, 22860, Mexico First published: 30 Nov 2016, 5(F1000 Faculty Rev):2801 ( Open Peer Review v1 https://doi.org/10.12688/f1000research.9679.1) Latest published: 30 Nov 2016, 5(F1000 Faculty Rev):2801 ( https://doi.org/10.12688/f1000research.9679.1) Reviewer Status Abstract Invited Reviewers Filamentous fungi have proven to be a better-suited model system than 1 2 3 unicellular yeasts in analyses of cellular processes such as polarized growth, exocytosis, endocytosis, and cytoskeleton-based organelle traffic. version 1 For example, the filamentous fungus Neurospora crassa develops a variety published of cellular forms. Studying the molecular basis of these forms has led to a 30 Nov 2016 better, yet incipient, understanding of polarized growth. Polarity factors as well as Rho GTPases, septins, and a localized delivery of vesicles are the central elements described so far that participate in the shift from isotropic F1000 Faculty Reviews are written by members of to polarized growth. The growth of the cell wall by apical biosynthesis and the prestigious F1000 Faculty. They are remodeling of polysaccharide components is a key process in hyphal commissioned and are peer reviewed before morphogenesis. The coordinated action of motor proteins and Rab publication to ensure that the final, published version GTPases mediates the vesicular journey along the hyphae toward the apex, where the exocyst mediates vesicle fusion with the plasma membrane. -
The Cricket As a Model Organism Hadley Wilson Horch • Taro Mito Aleksandar Popadic´ • Hideyo Ohuchi Sumihare Noji Editors
The Cricket as a Model Organism Hadley Wilson Horch • Taro Mito Aleksandar Popadic´ • Hideyo Ohuchi Sumihare Noji Editors The Cricket as a Model Organism Development, Regeneration, and Behavior Editors Hadley Wilson Horch Taro Mito Departments of Biology and Graduate school of Bioscience and Bioindustry Neuroscience Tokushima University Bowdoin College Tokushima, Japan Brunswick, ME, USA Aleksandar Popadic´ Hideyo Ohuchi Biological Sciences Department Department of Cytology and Histology Wayne State University Okayama University Detroit, MI, USA Okayama, Japan Dentistry and Pharmaceutical Sciences Sumihare Noji Okayama University Graduate School Graduate school of Bioscience of Medicine and Bioindustry Tokushima University Okayama, Japan Tokushima, Japan ISBN 978-4-431-56476-8 ISBN 978-4-431-56478-2 (eBook) DOI 10.1007/978-4-431-56478-2 Library of Congress Control Number: 2016960036 © Springer Japan KK 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. -
Weighing Falling Bodies. Galileo's Thought Experiment in The
Weighing Falling Bodies. Galileo’s Thought Experiment in the Development of his Dynamical Thinking. Maarten Van Dyck Centre for Logic and Philosophy of Science Centre for History of Science Ghent University [email protected] {The author is research assistant of the Fund for Scientific Research (FWO) – Flanders} 1 ACKNOWLEDGEMENTS I wish to thank Tim De Mey, without whom I would have never plunged so deep in Galileo’s thought experiment; Paolo Palmieri, who made the invaluable suggestion that I should have a look at the postils to Rocco , and whose comments on a first version of this paper helped to significantly improve both its contents and presentation; and Sabina Leonelli for her much appreciated assistance in translating the Italian fragments from the postils to Rocco. 2 CONTENTS 1. Introduction: The intelligibility of dynamics – the dynamics of intelligibility PART I – Understanding weight as a dynamic factor: Ambiguities 2. La bilancetta : Understanding mixtures and transforming gravities 2.a Solving the crown problem 2.b Balancing mixtures and speeds 3. De motu : Attempts at an Archimedean natural philosophy 3.a The dynamics of De motu 3.b From equal volumes to unit volumes 4. De motu : Introducing the thought experiment 4.a A hidden assumption 4.b The dynamical conundrum 5. Discorso : The impotence of specific gravity as a dynamic factor 5.a Moment and absolute weight 5.b Moment and specific weight 5.c The extrapolation argument PART II – Understanding weight as a dynamic factor: Towards a resolution 6. Postille a Roco : Rethinking the thought experiment 6.a Re-presenting the thought experiment 6.b Resolving the dynamical conundrum 7. -
Are Model Organisms Theoretical Models?
Are Model Organisms Theoretical Models? Veli-Pekka Parkkinen University of Bergen BIBLID [0873-626X (2017) 47; pp. 471–498] DOI: 10.1515/disp-2017-0015 Abstract This article compares the epistemic roles of theoretical models and model organisms in science, and specifically the role of non-human animal models in biomedicine. Much of the previous literature on this topic shares an assumption that animal models and theoretical models have a broadly similar epistemic role—that of indirect representation of a target through the study of a surrogate system. Recently, Levy and Currie (2015) have argued that model organism research and theoreti- cal modelling differ in the justification of model-to-target inferences, such that a unified account based on the widely accepted idea of model- ling as indirect representation does not similarly apply to both. I defend a similar conclusion, but argue that the distinction between animal models and theoretical models does not always track a difference in the justification of model-to-target inferences. Case studies of the use of animal models in biomedicine are presented to illustrate this. How- ever, Levy and Currie’s point can be argued for in a different way. I argue for the following distinction. Model organisms (and other con- crete models) function as surrogate sources of evidence, from which results are transferred to their targets by empirical extrapolation. By contrast, theoretical modelling does not involve such an inductive step. Rather, theoretical models are used for drawing conclusions from what is already known or assumed about the target system. Codifying as- sumptions about the causal structure of the target in external repre- sentational media (e.g. -
In the Later Philosophy of Paul Feyerabend
Durham E-Theses Pluralism and the 'Problem of Reality' in the Later Philosophy of Paul Feyerabend KIDD, IAN,JAMES How to cite: KIDD, IAN,JAMES (2010) Pluralism and the 'Problem of Reality' in the Later Philosophy of Paul Feyerabend, Durham theses, Durham University. Available at Durham E-Theses Online: http://etheses.dur.ac.uk/864/ Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in Durham E-Theses • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full Durham E-Theses policy for further details. Academic Support Oce, Durham University, University Oce, Old Elvet, Durham DH1 3HP e-mail: [email protected] Tel: +44 0191 334 6107 http://etheses.dur.ac.uk 2 Kidd Pluralism and the ‘Problem of Reality’ in the Later Philosophy of Paul Feyerabend Abstract Feyerabend’s later philosophy was a sustained defence of cultural and epistemic diversity. After Against Method (1975) Feyerabend argued that his rejection of methodological monism challenged the presumed unity and superiority of scientific knowledge and practices. His later philosophy was therefore dedicated to a reassessment of the merits of a wide range of ‘non-scientific’ traditions present throughout non-Western indigenous cultures. -
Understanding the Progress of Science
Understanding the Progress of Science C. D. McCoy 30 May 2018 The central problem of epistemology has always been and still is the problem of the growth of knowledge. And the growth of knowledge can be studied best by studying the growth of scientific knowledge. —(Popper, 2002b, xix) Merely fact-minded sciences make merely fact-minded people. —(Husserl, 1970, 6) The growth of human knowledge is realized most dramatically in the growth of scientific knowledge. What we have come to know through science about the workings of our human bodies and the workings of heavenly bodies, among much else, astounds, especially in comparison to our accumulating knowledge of the commonplace and everyday. Impressed by the evident epistemic progress made by science, many philosophers during the 20th century thought that studying how scientific knowledge increases is a crucial task of epistemological inquiry, and, indeed, the progress of science has been a topic of considerable interest. Yet, eventually, late in the century, attention waned and for the most part shifted to other tasks. Recently, however, a provocative article by Bird has re-ignited philosophical interest in the topic of scientific progress (Bird, 2007). Bird criticizes what he takes to have been the most prominent accounts advanced in the 20th century and presses for what he views as a venerable but lately overlooked one. He claims that realist philosophers of science have often presumed that truth is the goal of science and progress to be properly characterized by an accu- mulation of truth or truths, and notes that anti-realists have often rejected truth as a goal of science and characterized progress in terms of, among other things, “problem-solving effectiveness.”1 He criticizes the former for overlooking the relevance of justification to progress and the latter for giving up on truth. -
Philosophy in the Nineteenth Century
GEORGEMASON UNIVERSITY UNIVERSllY LIBRARIES THE OXFORD HANDBOOK OF GERMAN PHILOSOPHY IN THE NINETEENTH CENTURY ............................................................................................................................................................... Edited by MICHAEL N. FORSTER and KRISTIN GJESDAL OXFORD U N lV ERSITY PR ESS OXFORD UNIVERSITY PRESS Great Clarendon Street , Oxford, o:u 6oP, United Kingdom Oxford University Press is a depart ment of the t:niver,11r of Chford It furthers the University's obJective of excellence m n·s~·arch, s.:hol.1r,h1r , . and edu cation by publishing wor ldwide . Oxford is a regmereJ trade mJrk ,,t Oxford University Press m the IJK and in certain other countnc, © The several contribu tors 1015 The moral rights of the authors have been asserted First Edition pub!t,hed 10 2015 Impress ion 1 All rights reserved . No part of this publication may be rerroJuceJ. stored in a retrieval system, or transmitted, in any form or by any mea ns, without the prior permiss ion in writing of Oxford University Press, or as npreHl y pcrm1tteJ by law, by licence or under terms agreed with the arpropr1ate repr oi:raph1,, rights organi zation. Enquiries concerning reproduction outsi de th e swre of the above should be sent to the Rights Department, Oxford tJ111vers1ty Pre,,, at the address above You must not circulate this work in any other form and you must impo se this same condit ion on any .icqu irt'r Published in the United States of America by Oxford University l're,s 198 Madison Avenue , New York, NY wo16, United StJ tes of Amer tCJ British Library Cataloguing in Puhlication l>Jta Data availa ble Library of Congress Control Numher: 2014946121 ISBN 978- 0 -19-969654 - 3 Printed and boun d by CPI Gro up (UK) Ltd, Croydon, CRO 4YY Links to thud party websites are provided by Oxford in !(OOJ faith anJ for information only. -
ICOHTEC NEWSLETTER O N 176, December 2020
ICOHTEC NEWSLETTER No 176, December 2020 www.icohtec.org Sound To Light System Sound Operated Lamp Switch Circuit The first real dedicated disco lights were invented in about 1968 when someone decided to control lighting using electronics (Transistors and Thyristors in those days, no silicon chips) the idea was to flash lamps to different frequencies, originally three channels. Basically one lamp would flash in time with the Bass frequency, one in time with the Middle and one in time with the Treble. For the first time Sound To Light was born. The sound of the light: https://youtu.be/vkVPXpSE_Us Newsletter of the International Committee for the History of Technology - ICOHTEC Editor: Francesco Gerali, The University of Oklahoma School of Library and Information Studies. Norman, OK, United States. Mail to [email protected] Newsletter of the International Committee for the History of Technology - ICOHTEC Editor: Francesco Gerali, 2020 IEEE Pugh Visiting Scholar, IEEE History Center, NJ, United States. Mail to [email protected] I. ICOHTEC I.1 26TH INTERNATIONAL CONGRESS OF HISTORY OF SCIENCE AND TECHNOLOGY AND THE 48TH SYMPOSIUM OF ICOHTEC GO ONLINE I.2 MAURICE DAUMAS PRIZE - ICOHTEC’S ARTICLE PRIZE I.3 TURRIANO ICOHTEC PRIZE 2021 - CALL FOR SUBMISSIONS I.4 ICON II. PRIZES III. JOURNALS IV. E-SCHOL@RSHIP IN THE V. OPEN ACCESS VI. CALLS FOR MANUSCRIPTS VII. CALLS FOR PAPERS VIII. PLASTICIDADE, UMA HISTÓRIA DOS PLÁSTICOS EM PORTUGAL, A HISTORY OF PLASTICS IN PORTUGAL IX. JOBS, POSTDOCTORAL POSITIONS, AND RESEARCH FELLOWSHIPS X. JOIN ICOHTEC 1 I. ICOHTEC I.1 26th International Congress of History of Science and Technology and the 48th Symposium of ICOHTEC go online Dear Colleagues and Friends, Due to the risks of a real meeting, the organizers of the 26th International Congress of History of Science and Technology, ICHST (25 – 31 July 2021), decided to organize the conference online. -
Model Organisms Are Not (Theoretical) Models
Model Organisms are not (Theoretical) Models Arnon Levy and Adrian Currie Forthcoming in The British Journal for the Philosophy of Science. Abstract Many biological investigations are organized around a small group of species, often referred to as “model organisms”, such as the fruit fly Drosophila melanogaster. The terms “model” and “modeling” also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka-Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different epistemic characters. Theoretical modeling is grounded in explicit and known analogies between model and target. By contrast, inferences from model organisms are empirical extrapolations. Often such extrapolation is based on shared ancestry, sometimes in conjunction with other empirical information. One implication is that such inferences are unique to biology, whereas theoretical models are common across many disciplines. We close by discussing the diversity of uses to which model organisms are put, suggesting how these relate to our overall account. 1. Introduction 2. Volterra and Theoretical Modeling 3. Drosophila as a model organism 4. Generalizing from work on a model organisms 5. Phylogenetic inference and model organisms 6. Further roles of model organisms 6.1 Preparative experimentation. 6.2. Model organisms as paradigms 6.3. Model organisms as theoretical models. 6.4. Inspiration for engineers 6.5. Anchoring a research community. 7. Conclusion 1. Introduction Many biological investigations are organized around a small group of species, often referred to as “model organisms”, such as the bacterium Escherichia coli, the fruit fly Drosophila melanogaster and the house mouse, Mus musculus. -
GSA Response to NIH Request for Information On
Genetics Society of America Response to NIH Request for Information FY 2016-2020 Strategic Plan for the Office of Research Infrastructure Programs: Division of Comparative Medicine and Division of Construction and Instruments Programs Request for Information (NOT-OD-15-056) • Response Form Submitted March 16, 2015 Responses are limited to 1,500 characters per topic. All responses must be submitted by March 16, 2015. Disease Models, Informational Resources, and Other Resources Disease models, informational resources and other resources that should be modified or expanded in parallel with ongoing advances in biomedical research The Genetics Society of America (GSA) emphasizes the importance of model organisms for advancing knowledge in biomedical research. We believe that continued investment in model organisms—and the resources needed for supporting this research—is one of the most effective and efficient ways for NIH to continue to advance our understanding of living systems and improvement in human health. Model organism researchers depend upon shared community resources that serve the entire community, including stock centers and model organism databases, several of which depend upon ORIP funding. The long-term and consistent support of these community resources has been a crucial component of the strength and success of biomedical research in the United States and assures its future vigor. Centralized stock centers and databases provide optimal resource sharing that maximizes the return on the investments made by NIH and other government agencies. These community resources provide “off-the-shelf” research tools and thus increase the efficiency and speed of hypothesis-driven research supported by other grants. In addition, NIH support for these community resources allows them to operate on an open access model, thus assuring that all researchers have the tools they need for discovery. -
Arc of the Data Scientific Universe Leslie HDSR
The Arc of the Data Scientific Universe A comment on Sabina Leonelli’s “Data Science in Times of Pand(dem)ic” David Leslie, The Alan Turing Institute [email protected] To be published in Harvard Data Science Review (Winter 2021) Abstract In this paper explore the scaffolding of normative assumptions that supports Sabina Leonelli’s implicit appeal to the values of epistemic integrity and the global public good that conjointly animate the ethos of responsible and sustainable data work in the context of COVID-19. Drawing primarily on the writings of sociologist Robert K. Merton, the thinkers of the Vienna Circle, and Charles Sanders Peirce, I make some of these assumptions explicit by telling a longer story about the evolution of social thinking about the normative structure of science from Merton’s articulation of his well-known norms—those of universalism, communism, organized skepticism, and disinterestedness—to the present. I show that while Merton’s norms and his intertwinement of these with the underlying mechanisms of democratic order provide us with an especially good starting point to explore and clarify the commitments and values of science, Leonelli’s broader, more context-responsive, and more holistic vision of the epistemic integrity of data scientific understanding, and her discernment of the global and biospheric scope of its moral-practical reach, move beyond Merton’s schema in ways that effectively draw upon important critiques. Stepping past Merton, I argue that a combination of situated universalism, methodological pluralism, strong objectivity, and unbounded communalism must guide the responsible and sustainable data work of the future. -
Aspects of Theory-Ladenness in Data-Intensive Science1
Aspects of theory-ladenness in data-intensive science1 Wolfgang Pietsch2 Munich Center for Technology in Society, TU München, Munich, Germany Abstract Recent claims, mainly from computer scientists, concerning a largely automated and model- free data-intensive science have been countered by critical reactions from a number of philosophers of science. The debate suffers from a lack of detail in two respects, regarding (i) the actual methods used in data-intensive science and (ii) the specific ways in which these methods presuppose theoretical assumptions. I examine two widely-used algorithms, classificatory trees and non-parametric regression, and argue that these are theory-laden in an external sense, regarding the framing of research questions, but not in an internal sense concerning the causal structure of the examined phenomenon. With respect to the novelty of data-intensive science, I draw an analogy to exploratory as opposed to theory-directed experimentation. 1. Introduction Over the past decade, computer scientists have claimed that a new scientific methodology has become possible through advances in information technology (e.g. Gray 2007). This approach is supposed to be data-driven, strongly inductive, and relatively theory-independent. The epistemology of such data-intensive science has recently emerged as a novel topic in philosophy of science. Generally, the reactions have been rather critical, often referring to the more or less trivial observation that some kind of theory-ladenness always occurs in scientific research. But, as I will argue, this means throwing the baby out with the bathwater, since interesting shifts in the role of theory can indeed be observed when examining specific methods employed in data-intensive science.