911 research outputs found
Teaching Data Science
We describe an introductory data science course, entitled Introduction to
Data Science, offered at the University of Illinois at Urbana-Champaign. The
course introduced general programming concepts by using the Python programming
language with an emphasis on data preparation, processing, and presentation.
The course had no prerequisites, and students were not expected to have any
programming experience. This introductory course was designed to cover a wide
range of topics, from the nature of data, to storage, to visualization, to
probability and statistical analysis, to cloud and high performance computing,
without becoming overly focused on any one subject. We conclude this article
with a discussion of lessons learned and our plans to develop new data science
courses.Comment: 10 pages, 4 figures, International Conference on Computational
Science (ICCS 2016
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EthnoQuest: An interactive multimedia simulation for cultural anthropology fieldwork
EthnoQuest, an interactive multimedia CD-ROM simulating a visit to a fictional village named Amopan, was conceived as an adjunct to college-level classroom instruction in introductory anthropology courses. Since these classes typically involve large numbers of students, the logistics on conducting actual fieldwork pose serious problems for instructors and students alike. The conception of an engaging, interactive, accessible learning tool that incorporates appropriate pedagogical principles has found its ultimate expression in EthnoQuest
An Efficient Normalisation Procedure for Linear Temporal Logic and Very Weak Alternating Automata
In the mid 80s, Lichtenstein, Pnueli, and Zuck proved a classical theorem
stating that every formula of Past LTL (the extension of LTL with past
operators) is equivalent to a formula of the form , where
and contain only past operators. Some years later, Chang,
Manna, and Pnueli built on this result to derive a similar normal form for LTL.
Both normalisation procedures have a non-elementary worst-case blow-up, and
follow an involved path from formulas to counter-free automata to star-free
regular expressions and back to formulas. We improve on both points. We present
a direct and purely syntactic normalisation procedure for LTL yielding a normal
form, comparable to the one by Chang, Manna, and Pnueli, that has only a single
exponential blow-up. As an application, we derive a simple algorithm to
translate LTL into deterministic Rabin automata. The algorithm normalises the
formula, translates it into a special very weak alternating automaton, and
applies a simple determinisation procedure, valid only for these special
automata.Comment: This is the extended version of the referenced conference paper and
contains an appendix with additional materia
Mapping gene associations in human mitochondria using clinical disease phenotypes
Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes
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