scispace - formally typeset
Search or ask a question
Author

Paul Morris

Bio: Paul Morris is an academic researcher from University of Sheffield. The author has contributed to research in topics: Fractional flow reserve & Coronary artery disease. The author has an hindex of 49, co-authored 252 publications receiving 10739 citations. Previous affiliations of Paul Morris include Johns Hopkins University & Center for Complex Systems and Brain Sciences.


Papers
More filters
Journal ArticleDOI
Brian J. Haas1, Sophien Kamoun2, Sophien Kamoun3, Michael C. Zody1, Michael C. Zody4, Rays H. Y. Jiang5, Rays H. Y. Jiang1, Robert E. Handsaker1, Liliana M. Cano3, Manfred Grabherr1, Chinnappa D. Kodira6, Chinnappa D. Kodira1, Sylvain Raffaele3, Trudy Torto-Alalibo6, Trudy Torto-Alalibo2, Tolga O. Bozkurt3, Audrey M. V. Ah-Fong7, Lucia Alvarado1, Vicky L. Anderson8, Miles R. Armstrong9, Anna O. Avrova9, Laura Baxter10, Jim Beynon10, Petra C. Boevink9, Stephanie R. Bollmann11, Jorunn I. B. Bos2, Vincent Bulone12, Guohong Cai13, Cahid Cakir2, James C. Carrington14, Megan Chawner15, Lucio Conti16, Stefano Costanzo11, Richard Ewan16, Noah Fahlgren14, Michael A. Fischbach17, Johanna Fugelstad12, Eleanor M. Gilroy9, Sante Gnerre1, Pamela J. Green18, Laura J. Grenville-Briggs8, John Griffith15, Niklaus J. Grünwald11, Karolyn Horn15, Neil R. Horner8, Chia-Hui Hu19, Edgar Huitema2, Dong-Hoon Jeong18, Alexandra M. E. Jones3, Jonathan D. G. Jones3, Richard W. Jones11, Elinor K. Karlsson1, Sridhara G. Kunjeti20, Kurt Lamour21, Zhenyu Liu2, Li-Jun Ma1, Dan MacLean3, Marcus C. Chibucos22, Hayes McDonald23, Jessica McWalters15, Harold J. G. Meijer5, William Morgan24, Paul Morris25, Carol A. Munro8, Keith O'Neill1, Keith O'Neill6, Manuel D. Ospina-Giraldo15, Andrés Pinzón, Leighton Pritchard9, Bernard H Ramsahoye26, Qinghu Ren27, Silvia Restrepo, Sourav Roy7, Ari Sadanandom16, Alon Savidor28, Sebastian Schornack3, David C. Schwartz29, Ulrike Schumann8, Ben Schwessinger3, Lauren Seyer15, Ted Sharpe1, Cristina Silvar3, Jing Song2, David J. Studholme3, Sean M. Sykes1, Marco Thines3, Marco Thines30, Peter J. I. van de Vondervoort5, Vipaporn Phuntumart25, Stephan Wawra8, R. Weide5, Joe Win3, Carolyn A. Young2, Shiguo Zhou29, William E. Fry13, Blake C. Meyers18, Pieter van West8, Jean B. Ristaino19, Francine Govers5, Paul R. J. Birch31, Stephen C. Whisson9, Howard S. Judelson7, Chad Nusbaum1 
17 Sep 2009-Nature
TL;DR: The sequence of the P. infestans genome is reported, which at ∼240 megabases (Mb) is by far the largest and most complex genome sequenced so far in the chromalveolates and probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential.
Abstract: Phytophthora infestans is the most destructive pathogen of potato and a model organism for the oomycetes, a distinct lineage of fungus-like eukaryotes that are related to organisms such as brown algae and diatoms. As the agent of the Irish potato famine in the mid-nineteenth century, P. infestans has had a tremendous effect on human history, resulting in famine and population displacement(1). To this day, it affects world agriculture by causing the most destructive disease of potato, the fourth largest food crop and a critical alternative to the major cereal crops for feeding the world's population(1). Current annual worldwide potato crop losses due to late blight are conservatively estimated at $6.7 billion(2). Management of this devastating pathogen is challenged by its remarkable speed of adaptation to control strategies such as genetically resistant cultivars(3,4). Here we report the sequence of the P. infestans genome, which at similar to 240 megabases (Mb) is by far the largest and most complex genome sequenced so far in the chromalveolates. Its expansion results from a proliferation of repetitive DNA accounting for similar to 74% of the genome. Comparison with two other Phytophthora genomes showed rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes that are induced during infection or are predicted to have activities that alter host physiology. These fast-evolving effector genes are localized to highly dynamic and expanded regions of the P. infestans genome. This probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential.

1,341 citations

Journal ArticleDOI
01 Sep 2006-Science
TL;DR: Comparison of the two species' genomes reveals a rapid expansion and diversification of many protein families associated with plant infection such as hydrolases, ABC transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins with similarity to known oömycete avirulence genes.
Abstract: Draft genome sequences have been determined for the soybean pathogen Phytophthora sojae and the sudden oak death pathogen Phytophthora ramorum. Oomycetes such as these Phytophthora species share the kingdom Stramenopila with photosynthetic algae such as diatoms, and the presence of many Phytophthora genes of probable phototroph origin supports a photosynthetic ancestry for the stramenopiles. Comparison of the two species' genomes reveals a rapid expansion and diversification of many protein families associated with plant infection such as hydrolases, ABC transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins with similarity to known oomycete avirulence genes.

1,016 citations

Journal ArticleDOI
10 Dec 2010-Science
TL;DR: The genome sequence of the oomycete Hyaloperonospora arabidopsidis is reported, an obligate biotroph and natural pathogen of Arabidopsis thaliana, which exhibits dramatic reductions in genes encoding RXLR effectors, proteins associated with zoospore formation and motility, and enzymes for assimilation of inorganic nitrogen and sulfur.
Abstract: Many oomycete and fungal plant pathogens are obligate biotrophs, which extract nutrients only from living plant tissue and cannot grow apart from their hosts. Although these pathogens cause substantial crop losses, little is known about the molecular basis or evolution of obligate biotrophy. Here, we report the genome sequence of the oomycete Hyaloperonospora arabidopsidis (Hpa), an obligate biotroph and natural pathogen of Arabidopsis thaliana. In comparison with genomes of related, hemibiotrophic Phytophthora species, the Hpa genome exhibits dramatic reductions in genes encoding (i) RXLR effectors and other secreted pathogenicity proteins, (ii) enzymes for assimilation of inorganic nitrogen and sulfur, and (iii) proteins associated with zoospore formation and motility. These attributes comprise a genomic signature of evolution toward obligate biotrophy.

424 citations

Proceedings Article
Paul Morris1
11 Jul 1993
TL;DR: This paper describes an iterative improvement algorithm, called Breakout, that can escape from local minima, and proves that an idealized (but less efficient) version of the algorithm is complete.
Abstract: A number of algorithms have recently been proposed that use iterative improvement (a form of hill-climbing) to solve constraint satisfaction problems. These techniques have had dramatic success on certain problems. However, one factor limiting their wider application is the possibility of getting stuck at non-solution local minima. In this paper we describe an iterative improvement algorithm, called Breakout, that can escape from local minima. We present empirical evidence that this method is very effective in cases where previous approaches have difficulty. Although Breakout is not theoretically complete, in practice it appears to almost always find solutions, for solvable problems. We prove that an idealized (but less efficient) version of the algorithm is complete.

384 citations

Journal ArticleDOI
TL;DR: Access to the P. ultimum genome has revealed not only core pathogenic mechanisms within the oomycetes but also lineage-specific genes associated with the alternative virulence and lifestyles found within the pythiaceous lineages compared to the Peronosporaceae.
Abstract: Background Pythium ultimum is a ubiquitous oomycete plant pathogen responsible for a variety of diseases on a broad range of crop and ornamental species.

364 citations


Cited by
More filters
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Book
01 Jan 1988
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Abstract: From the Publisher: Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty—and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition—in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

15,671 citations

Journal ArticleDOI
TL;DR: Authors/Task Force Members: Piotr Ponikowski* (Chairperson) (Poland), Adriaan A. Voors* (Co-Chair person) (The Netherlands), Stefan D. Anker (Germany), Héctor Bueno (Spain), John G. F. Cleland (UK), Andrew J. S. Coats (UK)

13,400 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations