1,721,116 research outputs found
Todd Matthew Searle
No full textTodd Matthew Searle (Sept. 21, 1969-December 18, 1994) served in the US Air Force from 1988 to 1991 and was stationed in Okinawa, Japan
Experimental investigations of crack-trapping in brittle heterogeneous solids
No full textThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1994.Includes bibliographical references (p. 411-426).by Todd Matthew Mower.Ph.D
AI3SD Project: Predicting the Activity of Drug Candidates where there is No Target
No full textThis project aims to harness artificial intelligence and machine learning approaches to improve the discovery of new medicines. One of the most common situations in drug discovery is to know a molecule that possesses a desirable property and yet not to know how the molecule achieves that effect. The molecule needs improvement (often for things like how well it does its job, or how soluble it is in water) for it to be a realistic drug candidate and we must consider what changes need to be made. In this AI3SD project we know of molecules that efficiently kill the malaria parasite. The molecules need to be improved via small changes to their structures, yet we do not know the molecular biological target of these molecules. Without knowledge of the target it is impossible to design the improvements rationally. In such a project (known as “phenotypic drug discovery”) it is typically the case that the scientist will apply rules of thumb and intuition acquired over many related projects, in order to alter the structure of the molecule in search of those improvements. Yet it is also frequently the case that at such a stage of the project changes can be made to the molecule that accidentally obliterate the desired properties; most typically the molecules lose their potency against the pathogen. We will then have wasted time and resources making inactive molecules. On average each “fail” costs about two thousand pounds to make. It would be much more efficient if we could become more accurately predictive about which molecules need to be made. In our research consortium, Open Source Malaria (OSM), we have twice tried and failed to generate predictive models. There have occurred, in the period since, major new advances in AI and ML, particularly in the private sector. Since all of OSM’s data and ideas are freely shared in the public domain, it is possible for us to work with anyone in the generation of new models. We have therefore in this project used the AI3SD funds to run a predictive modelling competition and elicited contributions from amateurs and leading AI companies. Several models were better than the others and so, in a crucial part of this project, we asked those winners to predict new molecules, molecules that have never existed before, that they predict will be effective at killing the malaria parasite. We then went to the lab to validate these predictions by making the molecules suggested, and measuring how effective they are at killing the parasite in blood. The result of this was that three of the six predictions were active, a “hit rate” of about the same as the human hit rate across the rest of the project. Interestingly, these actives included a couple of molecules that the human chemists would probably not have tried. The end result of this work, aside from a new and predictive approach to the synthesis of antimalarial drug candidates, is be a case study of the actual capabilities of new AI/ML technologies in drug discovery: what works, what does not and an examination of why. Notably the project is still ongoing: since all the data and details of the approaches taken are in the public domain, others can try out their own predictive algorithms to see if they can do better
AI3SD Video: An Open Competition of People and Machines to Develop Predictive Models for Antimalarial Drug Discovery
No full textOne of the most promising series within the Open Source Malaria (OSM) consortium involves compounds that are active in the in vivo model of the disease. A molecular mechanism of action is strongly implicated, and is a mechanism shared with several leading antimalarials in the drug development pipeline, but no crystal structure has been obtained for the protein target. This OSM project is in the lead optimisation phase, with small changes being made to the structures synthesised. Yet even now many compounds designed by the human chemists are proving to be inactive, which can be wasteful of project resources. Over the last several years the consortium has run open competitions to see if the broader community can derive more predictive models for which molecules to synthesise. The most recent, funded by AI3SD, elicited high quality, open submissions from academia and several new companies specialising in artificial intelligence and machine learning. To close the loop, and examine the utility of these predictions, several of the novel structures proposed were synthesised and evaluated in a blood stage antimalarial assay. Were the machine-assisted predictions better than those derived from human intuition? An answer will be provided
Humans of AI3SD: Professor Matthew Todd
No full textThis interview forms part of our Humans of AI3SD Series. Professor Matthew Todd, a Professor of Drug Discovery from University College London was interviewed by Michelle Pauli at our AI3SD Network+ Conference in 2019. Matthew is a PI on one of the funding projects from AI3SD-FundingCall1
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Article : De l’imitation à la vénération : le culte de saint Wandrille et la réforme monastique au IXe siècle à Fontenelle
No full textArticle dans les Cahiers de civilisation médiévale, 2024/1, n°265, p.147-168Translation of the article by Todd Matthew Mattingly.Traduction de l'article de Todd Matthew Mattingly
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
- …
