Computational Methods for Gene Expression and Genomic Sequence Analysis

Advances in technologies currently produce more and more cost-effective, high-throughput, and large-scale biological data. As a result, there is an urgent need for developing efficient computational methods for analyzing these massive data. In this dissertation, we introduce methods to address several important issues in gene expression and genomic sequence analysis, two of the most important areas in bioinformatics.Firstly, we introduce a novel approach to predicting patterns of gene response to multiple treatments in case of small sample size. Researchers are increasingly interested in experiments with many treatments such as chemicals compounds or drug doses. However, due to cost, many experiments do not have large enough samples, making it difficult for conventional methods to predict patterns of gene response. Here we introduce an approach which exploited dependencies of pairwise comparisons outcomes and resampling techniques to predict true patterns of gene response in case of insufficient samples. This approach deduced more and better functionally enriched gene clusters than conventional methods. Our approach is therefore useful for multiple-treatment studies which have small sample size or contain highly variantly expressed genes.Secondly, we introduce a novel method for aligning short reads, which are DNA fragments extracted across genomes of individuals, to reference genomes. Results from short read alignment can be used for many studies such as measuring gene expression or detecting genetic variants. Here we introduce a method which employed an iterated randomized algorithm based on FM-index, an efficient data structure for full-text indexing, to align reads to the reference. This method improved alignment performance across a wide range of read lengths and error rates compared to several popular methods, making it a good choice for community to perform short read alignment.Finally, we introduce a novel approach to detecting genetic variants such as SNPs (single nucleotide polymorphisms) or INDELs (insertions/deletions). This study has great significance in a wide range of areas, from bioinformatics and genetic research to medical field. For example, one can predict how genomic changes are related to phenotype in their organism of interest, or associate genetic changes to disease risk or medical treatment efficacy. Here we introduce a method which leveraged known genetic variants existing in well-established databases to improve accuracy of detecting variants. This method had higher accuracy than several state-of-the-art methods in many cases, especially for detecting INDELs. Our method therefore has potential to be useful in research and clinical applications which rely on identifying genetic variants accurately

A High-Throughput Hardware Implementation of NAT Traversal For IPSEC VPN

In this paper, we present a high-throughput FPGA implementation of IPSec core. The core supports both NAT and non-NAT mode and can be used in high speed security gateway devices. Although IPSec ESP is very computing intensive for its cryptography process, our implementation shows that it can achieve high throughput and low lantency. The system is realized on the Zynq XC7Z045 from Xilinx and was verified and tested in practice. Results show that the design can gives a peak throughput of 5.721 Gbps for the IPSec ESP tunnel mode in NAT mode and 7.753 Gbps in non-NAT mode using one single AES encrypt core. We also compare the performance of the core when running in other mode of encryption

Toward production of jet fuel functionality in oilseeds: identification of FatB acyl-acyl carrier protein thioesterases and evaluation of combinatorial expression strategies in \u3ci\u3eCamelina\u3c/i\u3e seeds

Seeds of members of the genus Cuphea accumulate medium-chain fatty acids (MCFAs; 8:0–14:0). MCFA- and palmitic acid- (16:0) rich vegetable oils have received attention for jet fuel production, given their similarity in chain length to Jet A fuel hydrocarbons. Studies were conducted to test genes, including those from Cuphea, for their ability to confer jet fuel-type fatty acid accumulation in seed oil of the emerging biofuel crop Camelina sativa. Transcriptomes from Cuphea viscosissima and Cuphea pulcherrima developing seeds that accumulate \u3e90% of C8 and C10 fatty acids revealed three FatB cDNAs (CpuFatB3, CvFatB1, and CpuFatB4) expressed predominantly in seeds and structurally divergent from typical FatB thioesterases that release 16:0 from acyl carrier protein (ACP). Expression of CpuFatB3 and CvFatB1 resulted in Camelina oil with capric acid (10:0), and CpuFatB4 expression conferred myristic acid (14:0) production and increased 16:0. Co-expression of combinations of previously characterized Cuphea and California bay FatBs produced Camelina oils with mixtures of C8–C16 fatty acids, but amounts of each fatty acid were less than obtained by expression of individual FatB cDNAs. Increases in lauric acid (12:0) and 14:0, but not 10:0, in Camelina oil and at the sn-2 position of triacylglycerols resulted from inclusion of a coconut lysophosphatidic acid acyltransferase specialized for MCFAs. RNA interference (RNAi) suppression of Camelina β-ketoacyl-ACP synthase II, however, reduced 12:0 in seeds expressing a 12:0-ACP-specific FatB. Camelina lines presented here provide platforms for additional metabolic engineering targeting fatty acid synthase and specialized acyltransferases for achieving oils with high levels of jet fuel-type fatty acids

Toward production of jet fuel functionality in oilseeds: identification of FatB acyl-acyl carrier protein thioesterases and evaluation of combinatorial expression strategies in \u3ci\u3eCamelina\u3c/i\u3e seeds

Seeds of members of the genus Cuphea accumulate medium-chain fatty acids (MCFAs; 8:0–14:0). MCFA- and palmitic acid- (16:0) rich vegetable oils have received attention for jet fuel production, given their similarity in chain length to Jet A fuel hydrocarbons. Studies were conducted to test genes, including those from Cuphea, for their ability to confer jet fuel-type fatty acid accumulation in seed oil of the emerging biofuel crop Camelina sativa. Transcriptomes from Cuphea viscosissima and Cuphea pulcherrima developing seeds that accumulate \u3e90% of C8 and C10 fatty acids revealed three FatB cDNAs (CpuFatB3, CvFatB1, and CpuFatB4) expressed predominantly in seeds and structurally divergent from typical FatB thioesterases that release 16:0 from acyl carrier protein (ACP). Expression of CpuFatB3 and CvFatB1 resulted in Camelina oil with capric acid (10:0), and CpuFatB4 expression conferred myristic acid (14:0) production and increased 16:0. Co-expression of combinations of previously characterized Cuphea and California bay FatBs produced Camelina oils with mixtures of C8–C16 fatty acids, but amounts of each fatty acid were less than obtained by expression of individual FatB cDNAs. Increases in lauric acid (12:0) and 14:0, but not 10:0, in Camelina oil and at the sn-2 position of triacylglycerols resulted from inclusion of a coconut lysophosphatidic acid acyltransferase specialized for MCFAs. RNA interference (RNAi) suppression of Camelina β-ketoacyl-ACP synthase II, however, reduced 12:0 in seeds expressing a 12:0-ACP-specific FatB. Camelina lines presented here provide platforms for additional metabolic engineering targeting fatty acid synthase and specialized acyltransferases for achieving oils with high levels of jet fuel-type fatty acids

Toward production of jet fuel functionality in oilseeds: identification of FatB acyl-acyl carrier protein thioesterases and evaluation of combinatorial expression strategies in \u3ci\u3eCamelina\u3c/i\u3e seeds

Seeds of members of the genus Cuphea accumulate medium-chain fatty acids (MCFAs; 8:0–14:0). MCFA- and palmitic acid- (16:0) rich vegetable oils have received attention for jet fuel production, given their similarity in chain length to Jet A fuel hydrocarbons. Studies were conducted to test genes, including those from Cuphea, for their ability to confer jet fuel-type fatty acid accumulation in seed oil of the emerging biofuel crop Camelina sativa. Transcriptomes from Cuphea viscosissima and Cuphea pulcherrima developing seeds that accumulate \u3e90% of C8 and C10 fatty acids revealed three FatB cDNAs (CpuFatB3, CvFatB1, and CpuFatB4) expressed predominantly in seeds and structurally divergent from typical FatB thioesterases that release 16:0 from acyl carrier protein (ACP). Expression of CpuFatB3 and CvFatB1 resulted in Camelina oil with capric acid (10:0), and CpuFatB4 expression conferred myristic acid (14:0) production and increased 16:0. Co-expression of combinations of previously characterized Cuphea and California bay FatBs produced Camelina oils with mixtures of C8–C16 fatty acids, but amounts of each fatty acid were less than obtained by expression of individual FatB cDNAs. Increases in lauric acid (12:0) and 14:0, but not 10:0, in Camelina oil and at the sn-2 position of triacylglycerols resulted from inclusion of a coconut lysophosphatidic acid acyltransferase specialized for MCFAs. RNA interference (RNAi) suppression of Camelina β-ketoacyl-ACP synthase II, however, reduced 12:0 in seeds expressing a 12:0-ACP-specific FatB. Camelina lines presented here provide platforms for additional metabolic engineering targeting fatty acid synthase and specialized acyltransferases for achieving oils with high levels of jet fuel-type fatty acids

An efficient numerical procedure for calculating periodic vibrations of elastic mechanisms

This paper proposes a numerical procedure based on the well-known Newmark integration method to determine initial conditions for the periodic solution of a system of linear differential equations with time-periodic coefficients. Based on this, steady-state periodic vibrations of mechanisms with elastic elements governed by linearized differential equations with time-periodic coefficients can be conveniently calculated. The proposed procedure is demonstrated by a dynamic model of a planar four-bar mechanism with the flexible coupler