The objectives of this study were to investigate the effects of autoclave heating on the rumen protein degradation characteristics of flaxseed (<i>Linum usitatissimum</i>, cv. Vimy), and to compare them to differences in diffuse reflectance infrared Fourier transform (DRIFT) and Synchrotron based Fourier transform infrared microspectroscopy (S-FTIR) measurements of the protein alpha-helix to beta-sheet ratios. Hierarchical cluster analysis (CLA) and principal components analysis (PCA) were also conducted to identify differences in the DRIFT spectra. Flaxseed samples were kept raw for control or autoclaved in batches at 120°C for 20, 40 or 60 min for treatments 1, 2 and 3, respectively. The rumen degradation kinetics of protein were measured along with the protein sub-fractions of the Cornell net carbohydrate and protein system (CNCPS), and chemical composition. Intestinal digestibility was determined using the three-step procedure outlined by Calsamiglia and Stern (1995). Protein supply to the small intestine was determined using the NRC (2001) and DVE/OEB models. The results showed that heating increased dry matter (DM) and ether extract (EE) content, while reducing neutral detergent fibre (NDF) and acid detergent fibre (ADF), with little numerical difference between the three treatments. Soluble crude protein (SCP) also decreased upon autoclaving with concomitant increases in non-protein nitrogen (NPN), neutral detergent insoluble nitrogen (NDIN) and acid detergent insoluble nitrogen (ADIN). The CNCPS protein sub-fractions with the greatest changes were the buffer-soluble true protein fraction (PB1) and the fraction representing buffer-insoluble true protein which is not bound to NDF (PB2) showing dramatic increases, indicating a decrease in the overall protein degradability. <i>In situ</i>experiments showed a reduction in effective degradable dry matter (EDDM) as well as a reduction in effective degradable crude protein (EDCP) without significant differences between the treatments. Intestinal digestibility of protein as estimated by the three-step procedure showed no changes upon autoclaving. Modeling results, with flaxseed as the only feed source, for absorbable ruminally-undegraded feed protein in the intestines using both the NRC (2001) and DVE/OEB systems showed increases as a consequence of the autoclave treatments but again there were no differences between the treatments. The degraded protein balance results showed for both the NRC (2001) and DVE/OEB models that both were decreased upon autoclave treatment. However, the values for the NRC (2001) model suggested a potential nitrogen (N) deficiency and, therefore potentially impaired microbial crude protein (MCP) production, whereas the values for the DVE/OEB system showed potential N excess and, therefore, possible loss from the rumen. DRIFT analysis of protein secondary structure ratios showed a decrease in the alpha-helix to beta-sheet ratio for the whole seed, whereas results from S-FTIR spot data for cotyledon tissue showed autoclaving had the opposite effect on the ratio. CLA and PCA were successfully used to make distinctions between the different treatment spectra and showed enhanced sensitivity upon selection of a smaller spectral window to include only the amide I and II portion of the IR spectrum. The results failed to demonstrate any differences between the autoclave treatments used in this study, and showed that autoclaving generally decreased effectively ruminal degradability of flaxseed protein. The results further indicated that autoclaving had a significant enough effect on the flaxseed to permit identification of the altered alpha-helix to beta-sheet ratio with the mid-IR spectrum, as well as differentiation between the treatments using PCA and CLA. PCA and CLA results suggest that mid-IR spectral methods are more sensitive than traditional methods when used to identify differences between the heat treatments.

A phenomenon as complex as protein folding requires a complex model to approximate it. This thesis presents a bottom-up approach for building complex probabilistic models of protein secondary structure by incorporating the multiple information sources which we call experts. Expert opinions are represented by probability distributions over the set of possible structures. Bayesian treatment of a group of experts results in a consensus opinion that combines the experts' probability distributions using the operators of normalized product, quotient and exponentiation. The expression of this consensus opinion simplifiesto a product of the expert opinions with two assumptions: (1) balanced training of experts, i. e. , uniform prior probability over all structures, and (2) conditional independence between expert opinions,given the structure. This research also studies how Markov chains and hidden Markov models may be used to represent expert opinion. Closure properties areproven, and construction algorithms are given for product of hidden Markov models, and product, quotient and exponentiation of Markovchains. Algorithms for extracting single-structure predictions from these models are also given. Current product-of-experts approaches in machine learning are top-down modeling strategies that assume expert independence, and require simultaneous training of all experts. This research describes a bottom-up modeling strategy that can incorporate conditionally dependent experts, and assumes separately trained experts.

The objectives of this study were to investigate the effects of autoclave heating on the rumen protein degradation characteristics of flaxseed (<i>Linum usitatissimum</i>, cv. Vimy), and to compare them to differences in diffuse reflectance infrared Fourier transform (DRIFT) and Synchrotron based Fourier transform infrared microspectroscopy (S-FTIR) measurements of the protein alpha-helix to beta-sheet ratios. Hierarchical cluster analysis (CLA) and principal components analysis (PCA) were also conducted to identify differences in the DRIFT spectra. Flaxseed samples were kept raw for control or autoclaved in batches at 120°C for 20, 40 or 60 min for treatments 1, 2 and 3, respectively. The rumen degradation kinetics of protein were measured along with the protein sub-fractions of the Cornell net carbohydrate and protein system (CNCPS), and chemical composition. Intestinal digestibility was determined using the three-step procedure outlined by Calsamiglia and Stern (1995). Protein supply to the small intestine was determined using the NRC (2001) and DVE/OEB models. The results showed that heating increased dry matter (DM) and ether extract (EE) content, while reducing neutral detergent fibre (NDF) and acid detergent fibre (ADF), with little numerical difference between the three treatments. Soluble crude protein (SCP) also decreased upon autoclaving with concomitant increases in non-protein nitrogen (NPN), neutral detergent insoluble nitrogen (NDIN) and acid detergent insoluble nitrogen (ADIN). The CNCPS protein sub-fractions with the greatest changes were the buffer-soluble true protein fraction (PB1) and the fraction representing buffer-insoluble true protein which is not bound to NDF (PB2) showing dramatic increases, indicating a decrease in the overall protein degradability. <i>In situ</i>experiments showed a reduction in effective degradable dry matter (EDDM) as well as a reduction in effective degradable crude protein (EDCP) without significant differences between the treatments. Intestinal digestibility of protein as estimated by the three-step procedure showed no changes upon autoclaving. Modeling results, with flaxseed as the only feed source, for absorbable ruminally-undegraded feed protein in the intestines using both the NRC (2001) and DVE/OEB systems showed increases as a consequence of the autoclave treatments but again there were no differences between the treatments. The degraded protein balance results showed for both the NRC (2001) and DVE/OEB models that both were decreased upon autoclave treatment. However, the values for the NRC (2001) model suggested a potential nitrogen (N) deficiency and, therefore potentially impaired microbial crude protein (MCP) production, whereas the values for the DVE/OEB system showed potential N excess and, therefore, possible loss from the rumen. DRIFT analysis of protein secondary structure ratios showed a decrease in the alpha-helix to beta-sheet ratio for the whole seed, whereas results from S-FTIR spot data for cotyledon tissue showed autoclaving had the opposite effect on the ratio. CLA and PCA were successfully used to make distinctions between the different treatment spectra and showed enhanced sensitivity upon selection of a smaller spectral window to include only the amide I and II portion of the IR spectrum. The results failed to demonstrate any differences between the autoclave treatments used in this study, and showed that autoclaving generally decreased effectively ruminal degradability of flaxseed protein. The results further indicated that autoclaving had a significant enough effect on the flaxseed to permit identification of the altered alpha-helix to beta-sheet ratio with the mid-IR spectrum, as well as differentiation between the treatments using PCA and CLA. PCA and CLA results suggest that mid-IR spectral methods are more sensitive than traditional methods when used to identify differences between the heat treatments.

<p>This project is predicated on the ability of the boranophosphate modification of siRNA to increase its therapeutic applicability for gene silencing in in vitro and in vivo systems. It has been shown that the boranophosphate (BH3-PO3) can overcome many of the limitations that are traditionally found when using RNAi, namely nuclease stability. The synthesis of siRNA modified with 5'-(alpha-P-borano)-nucleoside triphosphates (NTP) analogs alone and in combination with 2'-deoxy-2'-fluoro nucleoside triphosphate analogs were performed and optimized. It was found that normal RNA transcriptions showed the highest yield with higher NTP concentrations and shorter incubation times. Boranophosphate modified RNA and 2'F/borano modified RNA transcription yield was optimal at lower NTP concentrations and extended incubations. The boranophosphate NTPs and RNA were characterized with high performance liquid chromatography, mass spectrometry, and nuclear magnetic resonance, indicating successful synthesis of NTPalphaB and 2'F NTPs. PAGE and mass spectrometry analysis were performed to ensure full-length transcription of the modified siRNA molecules. The effects of these modifications were explored with respect to the biophysical properties of the modified homoduplex and heteroduplex siRNA. The techniques used in this work included hybridization affinity assays (melting temperature), secondary structure determination (circular dichroism), nuclease stability assays, and assessment of the lipophilicity of the modified siRNA by determining partition coefficients. </p><p>Modification of siRNA with boranophosphate and 2'fluoro/borano modified NTPs appears to have caused the homoduplexes and heteroduplexes to adopt a more B form-like helix that had lower Tm compared to unmodified RNA. The stability of the siRNA transcript to enzymatic hydrolysis by Exonuclease T was on the order of 2'fluoro/borano> normal = boranophosphate. Boranophosphate modification increased the stability of the transcript to enzymatic hydrolysis by the endonuclease RNase A, compared to both normal and 2' fluoro modified siRNA. Overall, the 2' fluoro/borano modified siRNA showed the greatest biological stability. Modification of the siRNA with increasing percentages of boranophosphates resulted in increasing lipophilicity of the molecule up to 60-fold, compared to both normal and 2' fluoro RNA. </p><p>A method to site-specifically modify the boranophosphate siRNA using T4 RNA ligase was also investigated. Finally, the siRNA in this work was tested in several in vitro systems, yielding promising results for the usage of boranophosphate siRNA for use against human viruses and cancers. It was shown that in for in vitro systems for human papillomavirus gene expression (HeLa, SiHa, and W12E) and luciferase expression (B16F10 cells), boranophosphate modified siRNA can specifically downregulate gene expression, and in the case of human papillomavirus, can downregulate cell growth.</p> / Dissertation

The three-domain system is a biological classification of RNA. In bioinformatics, predicting the domain of RNA is helpful in the research of DNA and protein. By reviewing the related literatures, we notice that many researches are conducted for domain prediction with only the primary structure. However, compared with the primary structure, the secondary structure of an RNA contains more discriminative information. Therefore, we propose an SVM-based prediction algorithm that considers both the features of primary and secondary structures. In our experiment, we adopt 1606 RNA sequences from RNase P, 5S ribosomal RNA and snoRNA databases. The experimental results show that our algorithm achieves 96.39%, 95.70%, and 95.46% accuracies by combining three softwares of secondary structure prediction, pknotsRG, NUPACK, and RNAstructure, respectively. Thus, our method is a new effective approach for predicting the domain of an RNA sequence. The software implementation of our method, named RDP (RNA Domain Prediction), is available on the Web http://bio.cse.nsysu.edu.tw/RDP/.

Diapriids (Hymenoptera: Diapriidae) are small parasitic wasps. Though found throughout the world they are relatively unknown. A framework for advancing diapriid systematics is developed by introducing a new web-based application/database capable of storing a broad range of systematic data, and the first molecular phylogeny specifically focused at examining intrafamilial relationships. In addition to these efforts, a description of a new taxon is provided. Several advantages of digital description, including linking descriptions to an ontology of morphological terms, are highlighted. The functionality of the database is further illustrated in the production of a catalog of diapriid host associations. The hosts database currently holds over 450 association records, for over 500 named taxa (parasitoids and hosts), and over 180 references. Diapriids are found to be primarily endoparasitoids of Diptera emerging from the host pupa. Phylogenetic inference for a molecular dataset of 28S and 18S rRNA sequence data, derived from a diverse selection of diapriids, is accomplished with a new suite of tools developed for handling complex rRNA datasets. Several parsimony-based methodologies, including an alignment-free method of analyzing multiple sequences, are reviewed and applied using the new software tools. Diapriid phylogenetic relationships are shown to be broadly congruent with existing morphology-based classifications. Methods for analyzing typically excluded sequence data are shown to recover phylogenetic signal that would otherwise be lost and the alignment-free method performed remarkably well in this regard. Empirically, phylogenetic approaches that incorporate structural data were not notably different than those that did not.

It is well known that the biological function of a protein depends on its 3D structure. Therefore, solving the problem of protein structures is one of the most important works for studying proteins. However, protein structure prediction is a very challenging task because there is still no clear feature about how a protein folds to its 3D structure yet. In this thesis, we propose a genetic algorithm (GA) based on the lattice model to predict the 3D structure of an unknown protein, target protein, whose primary sequence and secondary structure elements (SSEs) are assumed known. Hydrophobic-hydrophilic model (HP model) is one of the most simplified and popular protein folding models. These models consider the hydrophobic-hydrophobic interactions of protein structures, but the results of prediction are still not encouraged enough. Therefore, we suggest that some other features should be considered, such as SSEs, charges, and disulfide bonds. That is, the fitness function of GA in our method considers not only how many hydrophobic-hydrophobic pairs there are, but also what kind of SSEs these amino acids belong to. The lattice model is in fact used to help us get a rough folding of the target protein, since we have no idea how they fold at the very beginning. We show that these additional features do improve the prediction accuracy by comparing our prediction results with their real structures with RMSD.

The comparison methods for RNA or protein molecules are important basic tools in molecular biology. So far, most comparison methods are only applicable to the primary structures of biomolecules, such as the sequence alignment and comparison methods. The functions of biomolecules have close relationship with their structures. The recent methods for finding the structures of biomolecules are NMR spectroscopy, X-ray crystallography, and prediction with computational simulation. There are many biomolecules with known structures, but their functions are unknown. The RNA secondary structure alignment problem is to align two RNA molecules to get the structure similarity, where their secondary structures are given. In addition, it is also helpful to predict the functions of biomolecules and to classify them. In this thesis, we design a dynamic programming method for aligning two RNA secondary structures which do not contain any pseudoknot. The time complexity of our algorithm is O(N4), where N is the number of blocks contained in the given RNA sequences. We also apply our algorithm to the real biomolecules, the tRNAs of Homo sapiens mitochondrion, to evaluate the practicability our method. We take three tRNA genes, TRNG, TRNA and TRNV, to test the performance of our algorithm. From the view point of human eyes, in fact, the structure of TRNG is more similar to TRNA. Our algorithm also gets this result. Hence, our algorithm provides an effective method to measure the similarity of two RNA secondary structures.

Ribonucleic acid (RNA) sometimes occurs in a complex structure called pseudoknots. Prediction of RNA secondary structures has drawn much attention from both biologists and computer scientists. Consequently, many useful tools have been developed for RNA secondary structure prediction, with or without pseudoknots. These tools have their individual strength and weakness. As a result, we propose a hybrid feature extraction method which integrates two prediction tools pknotsRG and NUPACK with a support vector machine (SVM). We first extract some useful features from the target RNA sequence, and then decide its prediction tool preference with SVM classification. Our test data set contains 723 RNA sequences, where 202 pseudoknotted RNA sequences are obtained from PseudoBase, and 521 nested RNA sequences are obtained from RNA SSTRAND. Experimental results show that our method improves not only the overall accuracy but also the sensitivity and the selectivity of the target sequences. Our method serves as a preprocessing process in analyzing RNA sequences before employing the RNA secondary structure prediction tools. The ability to combine the existing methods and make the prediction tools more accurate is our main contribution.

Multiple lines of evidence suggest that RNA performed all of the biological functions in the first life forms on earth. These functions included cleavage, ligation, polymerization, recognition, binding, and replication. In order to perform these functions, populations of RNA molecules with unevolved sequences must have been able to fold into compact three dimensional shapes, in unregulated environments, and without the help of proteins. Folding into compact tertiary structures is difficult because of the high charge density of RNA. Consequently, the ranges of temperature, salinity, pH, and pressure that allow RNA to fold into functional shapes is very restricted. We use thermodynamic arguments and Brownian dynamics simulations to compute the range of these environmental parameters that will allow RNA to fold. This is a non-trivial calculation due to the formation of an ion atmosphere around RNA that reduces its electric field. The results can be used to clarify the environments in which the transition to life is possible. Our preliminary calculations suggest that environments with low temperatures ($0-50^\circ C$) and high salt concentrations (greater than 100mM) are the most favorable for unassisted RNA folding and thus the transition to RNA-based life. Applications of our results include determining the environments on early earth where life formed, assesing the habitability of Europa, Titan, and (using modeled parameters) extrasolar planets. / text