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Search Results: 1 - 10 of 25293 matches for " Insuk Lee "
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An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae
Insuk Lee, Zhihua Li, Edward M. Marcotte
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000988
Abstract: Background Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations. Methodology/Principal Findings We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis. Conclusions/Significance YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org.
Characterising and Predicting Haploinsufficiency in the Human Genome
Ni Huang,Insuk Lee,Edward M. Marcotte,Matthew E. Hurles
PLOS Genetics , 2010, DOI: 10.1371/journal.pgen.1001154
Abstract: Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.
A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality
G Traver Hart, Insuk Lee, Edward M Marcotte
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-236
Abstract: Using an unsupervised probabilistic scoring scheme, we assigned a confidence score to each interaction in the matrix-model interpretation of the large-scale yeast mass-spectrometry data sets. The scoring metric proved more accurate than the filtering schemes used in the original data sets. We then took a high-confidence subset of these interactions and derived a set of complexes using MCL. The complexes show high correlation with existing annotations. Hierarchical organization of some protein complexes is evident from inter-complex interactions.We demonstrate that our scoring method can generate an integrated high-confidence subset of observed matrix-model interactions, which we subsequently used to derive an accurate map of yeast complexes. Our results indicate that essentiality is a product of the protein complex rather than the individual protein, and that we have achieved near saturation of the yeast high-abundance, rich-media-expressed "complex-ome."The molecular machines that carry out basic cellular processes are typically not individual proteins but protein complexes. Even in the relatively simple model organism Saccharomyces cerevisiae, most machines that process and store biological information are in fact large protein complexes comprised of many subunits.The path from measuring protein interactions to defining complexes has been well studied. Experimental and computational methods have provided over 50,000 putative yeast protein-protein interactions to date, although a substantial fraction of these may be spurious[1,2]. An array of analytical methods aimed at generating high-quality complexes from these data have been applied, including both unsupervised [3-5] and trained [6,7] techniques. Other genomic and proteomic data sets, such as gene expression, knockout phenotype, subcellular localization, and genetic interaction profiles, and phylogenetic profiles [5,6,8-10], have also been integrated with the raw interaction data in an effort to broaden and dee
Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes
Kriston L McGary, Insuk Lee, Edward M Marcotte
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-12-r258
Abstract: Geneticists have long observed that mutations that lead to the same organismal phenotype are typically functionally related, and have interpreted epistatic relationships between genes as genetic pathways and more recently as gene networks. In the post-genomic period, an abundance of high-throughput data has encouraged the construction of functional networks [1], which integrate evidence from a wide variety of experiments to infer functional relationships between genes. Historically, mutations that lead to the same phenotype were inferred to be functionally linked; now, with extensive functional networks, we ask whether the inverse is also true. If gene loss-of-function phenotypes could be successfully inferred on the basis of linkages in functional gene networks, then this would enable the directed extension of genetic screens and open the possibility to apply similar approaches in humans for the direct identification of disease genes.In particular, important advances over the past decade in both forward and reverse genetics mean that such predictability could be exploited in a straightforward manner to associate specific genes with phenotypes. In terms of forward genetics, genome-wide association studies (for review, see [2]) are showing great power for identifying candidate genes associated with human traits and diseases, such as recent studies correlating variants in the ORMDL3 gene with risk for childhood asthma [3]. In terms of reverse genetics, rapid testing of candidate genes has become more routine because of availability of mutant strain collections (for example, yeast deletion strain collections [4,5]) as well as the relative ease of RNA interference downregulation of genes (as, for instance, for genome-wide RNA interference screens of Caenorhabtidis elegans [6,7] or human cell lines; for review [8]). The prediction of loss-of-function phenotypes would bridge these two aspects of genetics; given an initial set of genes associated with a phenotype of intere
Inductive Detection of Magnetostrictive Resonance
Jang-ik Park,SangGap Lee,Insuk Yu,Yongho Seo
Physics , 2006,
Abstract: We have developed an inductive method to detect the magnetostrictive resonance signal and applied it to an ultrasonic magnetostrictive transducer sample. Slab shaped ferrite samples are mounted in an RF coil and actuated by pulse modulated RF magnetic field. A DC magnetic field is also applied and the resonance signal from the sample is detected by the same coil after the RF field is turned off. The detector system is similar to a conventional pulse NMR system with quadrature detection. The detected signal is sensitive to the bias DC field strength and direction as well as the dimension of the sample.
Circular Kinks on the Surface of Granular Material Rotated in a Tilted Spinning Bucket
Sangsoo Yoon,Byeong-ho Eom,Jysoo Lee,Insuk Yu
Physics , 1999, DOI: 10.1103/PhysRevLett.82.4639
Abstract: We find that circular kinks form on the surface of granular material when the axis of rotation is tilted more than the angle of internal friction of the material. Radius of the kinks is measured as a function of the spinning speed and the tilting angle. Stability consideration of the surface results in an explanation that the kink is a boundary between the inner unstable and outer stable regions. A simple cellular automata model also displays kinks at the stability boundary.
Scaling Limit of Two-component Interacting Brownian Motions
Insuk Seo
Mathematics , 2015,
Abstract: This paper presents our study of the asymptotic behavior of a two-component system of Brownian motions undergoing certain singular interactions. In particular, the system is a combination of two different types of particles and the mechanical properties and interaction parameters depend on the corresponding type of particles. We prove that the hydrodynamic limit of the empirical densities of two types is the solution of a certain quasi-linear parabolic partial differential equation known as the Maxwell-Stefan equation.
Large Deviation Principle for Interacting Brownian Motions
Insuk Seo
Mathematics , 2015,
Abstract: We prove the Large Deviation Principle for the empirical process in a system of locally interacting Brownian motions in the nonequilibrium dynamic. Such a phenomenon has been proven only for two lattice systems: the symmetric simple exclusion process and zero-range process. Therefore, we have achieved the third result in this context and moreover the first result for the diffusion-type interacting particle system.
Rational Extension of the Ribosome Biogenesis Pathway Using Network-Guided Genetics
Zhihua Li,Insuk Lee,Emily Moradi,Nai-Jung Hung,Arlen W. Johnson,Edward M. Marcotte
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.1000213
Abstract: Biogenesis of ribosomes is an essential cellular process conserved across all eukaryotes and is known to require >170 genes for the assembly, modification, and trafficking of ribosome components through multiple cellular compartments. Despite intensive study, this pathway likely involves many additional genes. Here, we employ network-guided genetics—an approach for associating candidate genes with biological processes that capitalizes on recent advances in functional genomic and proteomic studies—to computationally identify additional ribosomal biogenesis genes. We experimentally evaluated >100 candidate yeast genes in a battery of assays, confirming involvement of at least 15 new genes, including previously uncharacterized genes (YDL063C, YIL091C, YOR287C, YOR006C/TSR3, YOL022C/TSR4). We associate the new genes with specific aspects of ribosomal subunit maturation, ribosomal particle association, and ribosomal subunit nuclear export, and we identify genes specifically required for the processing of 5S, 7S, 20S, 27S, and 35S rRNAs. These results reveal new connections between ribosome biogenesis and mRNA splicing and add >10% new genes—most with human orthologs—to the biogenesis pathway, significantly extending our understanding of a universally conserved eukaryotic process.
RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network
Peggy I Wang, Sohyun Hwang, Rodney P Kincaid, Christopher S Sullivan, Insuk Lee, Edward M Marcotte
Genome Biology , 2012, DOI: 10.1186/gb-2012-13-12-r125
Abstract:
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