445 research outputs found
SeqGene: a comprehensive software solution for mining exome- and transcriptome- sequencing data
Get PDFAbstract Background The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide range of analysis tasks. Results SeqGene, a new data mining tool, supports mutation detection and annotation, dbSNP and 1000 Genome data integration, RNA-Seq expression quantification, mutation and coverage visualization, allele specific expression (ASE), differentially expressed genes (DEGs) identification, copy number variation (CNV) analysis, and gene expression quantitative trait loci (eQTLs) detection. We also developed novel methods for testing the association between SNP and expression and identifying genotype-controlled DEGs. We showed that the results generated from SeqGene compares favourably to other existing methods in our case studies. Conclusion SeqGene is designed as a general-purpose software package. It supports both paired-end reads and single reads generated on most sequencing platforms; it runs on all major types of computers; it supports arbitrary genome assemblies for arbitrary organisms; and it scales well to support both large and small scale sequencing projects. The software homepage is http://seqgene.sourceforge.net.</p
A Computational Approach to Reconstructing Gene Regulatory Networks.
Get PDFMotivation: Many modeling frameworks have been applied to infer regulatory networks from gene expression data sets. Linear Additive Models (LAMs), as one large category of models, have been gaining more and more popularity. One problem associated with this kind of models is that the system is often under-determined because of excessive number of unknown parameters. In addition, the practical utility of these models has remained unclear. Methods: Based on LAMs, we developed an improved method to infer gene regulatory networks from time-series gene expression data sets. The method includes an incremental connectivity model with indexed regulatory elements and a linear time complexity fitting algorithm embedded with genetic algorithm. Comparing to previous LAMs, where a fully connected model is used, the new technique reduces the number of parameters by O(N), therefore increasing the chance of recovering the underlying regulatory network. The fitting algorithm increment the connectivity during the fitting process until a satisfactory fit is obtained. Results: We performed a systematic study to explore the data mining availability of LAMs. A guideline to use LAMs is provided: If the system is small (3-20 elements), more than 90% regulation pathways can be correctly determined. For a large scale system, either a clustering is needed or it is necessary to integrate other information besides expression profile only. Coupled with clustering method, we applied our method to Rat Central Nervous System development (CNS) data with 112 genes. We were able to efficiently generate regulatory networks with statistically significant pathways which have been previously predicted
Frequency range for stable generation of atmospheric glow discharges in He and N2
No full textSummary form only given, as follows. We aim to study the effects of the temporal characteristics of the excitation on atmospheric plasma dynamics. In particular we establish the frequency range within which stable atmospheric glow discharges can be generated with sinusoidal excitation. We consider both a helium discharge and nitrogen discharge, such that the difference of discharge dynamics in these two different gases is used to probe the physics that underscores their different frequency ranges. Using a theoretical model that has been validated with experiments, atmospheric helium discharges and atmospheric nitrogen discharges are studied in detail. Through numerical examples, their respective frequency ranges for stable generation of atmospheric glow discharges are deduced. The difference in these frequency ranges is discussed from the standpoint of the difference in key ionization processes in these two different carrier gases. These are also compared with experimental results
A Fast Iterative Algorithm for Identifying Feature Scales and Signed Fuzzy Measures in Generalized Choquet Integrals
No full textEffects of bacterial physiological state and surface population in nonthermal atmospheric microplasma inactivation
No full textEffects of bacterial physiological state and surface population in nonthermal atmospheric microplasma inactivatio
Surface protein destruction using cold atmospheric plasmas
No full textSurface protein destruction using cold atmospheric plasma
Introduction to the Development and Validation of Predictive Biomarker Models from High-Throughput Data Sets
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