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Search Results: 1 - 10 of 37324 matches for " Christopher Lee "
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Early Exposure to Environmental Toxin Contributes to Neuronal Vulnerability and Axonal Pathology in a Model of Familial ALS  [PDF]
Grace Lee, Christopher A. Shaw
Neuroscience & Medicine (NM) , 2012, DOI: 10.4236/nm.2012.34050
Abstract: Adult onset amyotrophic lateral sclerosis (ALS) arises due to progressive and irreversible functional deficits to the central nervous system, specifically the loss of motor neurons. Sporadic ALS causality is not well understood, but is almost certainly of multifactorial origin involving a combination of genetic and environmental factors. The discovery of endemic ALS in the native Chamorro population of Guam during the 1950s and the co-occurrence of Parkinsonism and dementia in some patients led to searches for environmental toxins that could be responsible. In the present paper, we report that an environmental neurotoxin enhances mutant superoxide dismutase (SOD)-induced spinal motor neuron death and pathology and induces motor axon abnormalities. These results cumulatively confirm earlier findings that exposure to an environmental toxin is sufficient to produce the disease phenotype and indicate a role for gene-environment interaction in some forms of the disease.
Empirical Information Metrics for Prediction Power and Experiment Planning
Christopher Lee
Information , 2011, DOI: 10.3390/info2010017
Abstract: In principle, information theory could provide useful metrics for statistical inference. In practice this is impeded by divergent assumptions: Information theory assumes the joint distribution of variables of interest is known, whereas in statistical inference it is hidden and is the goal of inference. To integrate these approaches we note a common theme they share, namely the measurement of prediction power. We generalize this concept as an information metric, subject to several requirements: Calculation of the metric must be objective or model-free; unbiased; convergent; probabilistically bounded; and low in computational complexity. Unfortunately, widely used model selection metrics such as Maximum Likelihood, the Akaike Information Criterion and Bayesian Information Criterion do not necessarily meet all these requirements. We define four distinct empirical information metrics measured via sampling, with explicit Law of Large Numbers convergence guarantees, which meet these requirements: Ie, the empirical information, a measure of average prediction power; Ib, the overfitting bias information, which measures selection bias in the modeling procedure; Ip, the potential information, which measures the total remaining information in the observations not yet discovered by the model; and Im, the model information, which measures the model’s extrapolation prediction power. Finally, we show that Ip + Ie, Ip + Im, and Ie — Im are fixed constants for a given observed dataset (i.e. prediction target), independent of the model, and thus represent a fundamental subdivision of the total information contained in the observations. We discuss the application of these metrics to modeling and experiment planning. ? ?
Universal Nonperturbative Effects in Event Shapes from Soft-Collinear Effective Theory
Lee, Christopher
High Energy Physics - Phenomenology , 2007, DOI: 10.1142/S021773230702289X
Abstract: Two-jet event shape distributions, traditionally studied in the language of perturbative QCD, can be described naturally in soft-collinear effective theory. In this language, we demonstrate factorization of event shape distributions into perturbatively-calculable hard and jet functions and nonperturbative soft functions, and show how the latter contribute universal shifts to the mean values of various event shape distributions. Violations of universality in shifts of higher moments can give information on correlations of energy flow in soft radiation.
Open Peer Review by a Selected-Papers Network
Christopher Lee
Frontiers in Computational Neuroscience , 2012, DOI: 10.3389/fncom.2012.00001
Abstract: A selected-papers (SP) network is a network in which researchers who read, write, and review articles subscribe to each other based on common interests. Instead of reviewing a manuscript in secret for the Editor of a journal, each reviewer simply publishes his review (typically of a paper he wishes to recommend) to his SP network subscribers. Once the SP network reviewers complete their review decisions, the authors can invite any journal editor they want to consider these reviews and initial audience size, and make a publication decision. Since all impact assessment, reviews, and revisions are complete, this decision process should be short. I show how the SP network can provide a new way of measuring impact, catalyze the emergence of new subfields, and accelerate discovery in existing fields, by providing each reader a fine-grained filter for high-impact. I present a three phase plan for building a basic SP network, and making it an effective peer review platform that can be used by journals, conferences, users of repositories such as arXiv, and users of search engines such as PubMed. I show how the SP network can greatly improve review and dissemination of research articles in areas that are not well-supported by existing journals. Finally, I illustrate how the SP network concept can work well with existing publication services such as journals, conferences, arXiv, PubMed, and online citation management sites.
The Evolution of Soft Collinear Effective Theory
Christopher Lee
Physics , 2014, DOI: 10.1142/S2010194515600459
Abstract: Soft Collinear Effective Theory (SCET) is an effective field theory of Quantum Chromodynamics (QCD) for processes where there are energetic, nearly lightlike degrees of freedom interacting with one another via soft radiation. SCET has found many applications in high-energy and nuclear physics, especially in recent years the physics of hadronic jets in $e^+e^-$, lepton-hadron, hadron-hadron, and heavy-ion collisions. SCET can be used to factorize multi-scale cross sections in these processes into single-scale hard, collinear, and soft functions, and to evolve these through the renormalization group to resum large logarithms of ratios of the scales that appear in the QCD perturbative expansion, as well as to study properties of nonperturbative effects. We overview the elementary concepts of SCET and describe how they can be applied in high-energy and nuclear physics.
Distinguishing Functional Amino Acid Covariation from Background Linkage Disequilibrium in HIV Protease and Reverse Transcriptase
Qi Wang, Christopher Lee
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000814
Abstract: Correlated amino acid mutation analysis has been widely used to infer functional interactions between different sites in a protein. However, this analysis can be confounded by important phylogenetic effects broadly classifiable as background linkage disequilibrium (BLD). We have systematically separated the covariation induced by selective interactions between amino acids from background LD, using synonymous (S) vs. amino acid (A) mutations. Covariation between two amino acid mutations, (A,A), can be affected by selective interactions between amino acids, whereas covariation within (A,S) pairs or (S,S) pairs cannot. Our analysis of the pol gene — including the protease and the reverse transcriptase genes — in HIV reveals that (A,A) covariation levels are enormously higher than for either (A,S) or (S,S), and thus cannot be attributed to phylogenetic effects. The magnitude of these effects suggests that a large portion of (A,A) covariation in the HIV pol gene results from selective interactions. Inspection of the most prominent (A,A) interactions in the HIV pol gene showed that they are known sites of independently identified drug resistance mutations, and physically cluster around the drug binding site. Moreover, the specific set of (A,A) interaction pairs was reproducible in different drug treatment studies, and vanished in untreated HIV samples. The (S,S) covariation curves measured a low but detectable level of background LD in HIV.
Negative selection pressure against premature protein truncation is reduced by both alternative splicing and diploidy
Yi Xing, Christopher Lee
Genome Biology , 2004, DOI: 10.1186/gb-2004-5-6-p12
Evidence of functional selection pressure for alternative splicingevents that accelerate evolution of protein subsequences
Yi Xing, Christopher Lee
Genome Biology , 2005, DOI: 10.1186/gb-2005-6-5-p8
Abstract: Additional data file 1.
Analysis of alternative splicing with microarrays: successes and challenges
Christopher Lee, Meenakshi Roy
Genome Biology , 2004, DOI: 10.1186/gb-2004-5-7-231
Abstract: The field of genomics is sometimes accused of being largely a numbers game - increasing our knowledge quantitatively without adding qualitatively to our conceptual understanding. But sometimes big numbers change our mental models. One area in which genomic data appear to be causing just such a shift is the field of alternative splicing. The 'one gene, one product' dogma of molecular biology is yielding in the face of large amounts of human genome data to 'most genes have multiple products', with important implications throughout biology [1-6]. Recently, several large-scale studies [7-9] have shown that alternative splicing can be analyzed in a high-throughput manner using DNA-microarray methods, an approach that is likely to be useful for understanding the role of alternative splicing in many areas of biology.Bioinformatic analyses of expressed sequence tag (EST) data were the first to herald the alternative-splicing revolution. A number of studies by different groups all reported finding alternative splice forms in a surprisingly large fraction of human genes, ranging from 40% to 60% [10-15]. These studies have identified more than 30,000 alternative splice forms in human, effectively doubling the number of human gene products relative to the estimated 32,000 human genes. But EST data clearly do not tell the whole story. Even assuming that a wide variety of potential problems are carefully filtered out (for example, genomic contamination and incomplete mRNA processing; see [16]), the very nature of the EST data leaves many questions unanswered. Individual ESTs might represent rare splice forms (or even errors made by the splicing machinery) that do not constitute a significant fraction of the gene's transcripts in living cells. EST sequencing also has some bias and does not evenly cover every part of every gene. One basic constraint on the discovery of alternative splice forms is that there simply aren't enough EST data to give good coverage of most gene regions in
Distinguishing HIV-1 drug resistance, accessory, and viral fitness mutations using conditional selection pressure analysis of treated versus untreated patient samples
Lamei Chen, Christopher Lee
Biology Direct , 2006, DOI: 10.1186/1745-6150-1-14
Abstract: We have applied this analysis to four independent HIV protease sequencing datasets: 50,000 clinical samples sequenced by Specialty Laboratories, Inc.; 1800 samples from patients treated with protease inhibitors; 2600 samples from untreated patients; 400 samples from untreated African patients. We have identified 428 mutation interactions in Specialty dataset with statistical significance and we were able to distinguish primary vs. accessory mutations for many well-studied examples. Amino acid interactions identified by conditional Ka/Ks matched 80 of 92 pair wise interactions found by a completely independent study of HIV protease (p-value for this match is significant: 10-70). Furthermore, Ka/Ks selection pressure results were highly reproducible among these independent datasets, both qualitatively and quantitatively, suggesting that they are detecting real drug-resistance and viral fitness mutations in the wild HIV-1 population.Conditional Ka/Ks analysis can detect mutation interactions and distinguish primary vs. accessory mutations in HIV-1. Ka/Ks analysis of treated vs. untreated patient data can distinguish drug-resistance vs. viral fitness mutations. Verification of these results would require longitudinal studies. The result provides a valuable resource for AIDS research and will be available for open access upon publication at http://www.bioinformatics.ucla.edu/HIV webciteThis article was reviewed by Wen-Hsiung Li (nominated by Eugene V. Koonin), Robert Shafer (nominated by Eugene V. Koonin), and Shamil Sunyaev.Reviewed by Wen-Hsiung Li (nominated by Eugene V. Koonin), Robert Shafer (nominated by Eugene V. Koonin), and Shamil Sunyaev. For the full reviews, please go to the Reviewers’ comments section.During the past two decades, researchers and clinicians have made enormous efforts to identify drug resistance mutations in HIV-1 protease, a major target of anti-retroviral therapy. Discovery of a new drug resistance mutation typically requires a combination o
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