Matching Items (23)
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
Specific dendritic morphologies are a hallmark of neuronal identity, circuit assembly, and behaviorally relevant function. Despite the importance of dendrites in brain health and disease, the functional consequences of dendritic shape remain largely unknown. This dissertation addresses two fundamental and interrelated aspects of dendrite neurobiology. First, by utilizing the genetic power of Drosophila melanogaster, these studies assess the developmental mechanisms underlying single neuron morphology, and subsequently investigate the functional and behavioral consequences resulting from developmental irregularity. Significant insights into the molecular mechanisms that contribute to dendrite development come from studies of Down syndrome cell adhesion molecule (Dscam). While these findings have been garnered primarily from sensory neurons whose arbors innervate a two-dimensional plane, it is likely that the principles apply in three-dimensional central neurons that provide the structural substrate for synaptic input and neural circuit formation. As such, this dissertation supports the hypothesis that neuron type impacts the realization of Dscam function. In fact, in Drosophila motoneurons, Dscam serves a previously unknown cell-autonomous function in dendrite growth. Dscam manipulations produced a range of dendritic phenotypes with alteration in branch number and length. Subsequent experiments exploited the dendritic alterations produced by Dscam manipulations in order to correlate dendritic structure with the suggested function of these neurons. These data indicate that basic motoneuron function and behavior are maintained even in the absence of all adult dendrites within the same neuron. By contrast, dendrites are required for adjusting motoneuron responses to specific challenging behavioral requirements. Here, I establish a direct link between dendritic structure and neuronal function at the level of the single cell, thus defining the structural substrates necessary for conferring various aspects of functional motor output. Taken together, information gathered from these studies can inform the quest in deciphering how complex cell morphologies and networks form and are precisely linked to their function.
ContributorsHutchinson, Katie Marie (Author) / Duch, Carsten (Thesis advisor) / Neisewander, Janet (Thesis advisor) / Newfeld, Stuart (Committee member) / Smith, Brian (Committee member) / Orchinik, Miles (Committee member) / Arizona State University (Publisher)
Created2013
Description
The entire history of HIV-1 is hidden in its ten thousand bases, where information regarding its evolutionary traversal through the human population can only be unlocked with fine-scale sequence analysis. Measurable footprints of mutation and recombination have imparted upon us a wealth of knowledge, from multiple chimpanzee-to-human transmissions to patterns of neutralizing antibody and drug resistance. Extracting maximum understanding from such diverse data can only be accomplished by analyzing the viral population from many angles. This body of work explores two primary aspects of HIV sequence evolution, point mutation and recombination, through cross-sectional (inter-individual) and longitudinal (intra-individual) investigations, respectively. Cross-sectional Analysis: The role of Haiti in the subtype B pandemic has been hotly debated for years; while there have been many studies, up to this point, no one has incorporated the well-known mechanism of retroviral recombination into their biological model. Prior to the use of recombination detection, multiple analyses produced trees where subtype B appears to have first entered Haiti, followed by a jump into the rest of the world. The results presented here contest the Haiti-first theory of the pandemic and instead suggest simultaneous entries of subtype B into Haiti and the rest of the world. Longitudinal Analysis: Potential N-linked glycosylation sites (PNGS) are the most evolutionarily dynamic component of one of the most evolutionarily dynamic proteins known to date. While the number of mutations associated with the increase or decrease of PNGS frequency over time is high, there are a set of relatively stable sites that persist within and between longitudinally sampled individuals. Here, I identify the most conserved stable PNGSs and suggest their potential roles in host-virus interplay. In addition, I have identified, for the first time, what may be a gp-120-based environmental preference for N-linked glycosylation sites.
ContributorsHepp, Crystal Marie, 1981- (Author) / Rosenberg, Michael S. (Thesis advisor) / Hedrick, Philip (Committee member) / Escalante, Ananias (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
In somatic cells, the mitotic spindle apparatus is centrosomal and several isoforms of Protein Kinase C (PKC) have been associated with the mitotic spindle, but their role in stabilizing the mitotic spindle is unclear. Other protein kinases such as, Glycogen Synthase Kinase 3â (GSK3â) also have been shown to be associated with the mitotic spindle. In the study in chapter 2, we show the enrichment of active (phosphorylated) PKCæ at the centrosomal region of the spindle apparatus in metaphase stage of 3T3 cells. In order to understand whether the two kinases, PKC and GSK3â are associated with the mitotic spindle, first, the co-localization and close molecular proximity of PKC isoforms with GSK3â was studied in metaphase cells. Second, the involvement of inactive GSK3â in maintaining an intact mitotic spindle was shown. Third, this study showed that addition of a phospho-PKCæ specific inhibitor to cells can disrupt the mitotic spindle microtubules. The mitotic spindle at metaphase in mouse fibroblasts appears to be maintained by PKCæ acting through GSK3â. The MAPK pathway has been implicated in various functions related to cell cycle regulation. MAPKK (MEK) is part of this pathway and the extracellular regulated kinase (ERK) is its known downstream target. GSK3â and PKCæ also have been implicated in cell cycle regulation. In the study in chapter 3, we tested the effects of inhibiting MEK on the activities of ERK, GSK3â, PKCæ, and á-tubulin. Results from this study indicate that inhibition of MEK did not inhibit GSK3â and PKCæ enrichment at the centrosomes. However, the mitotic spindle showed a reduction in the pixel intensity of microtubules and also a reduction in the number of cells in each of the M-phase stages. A peptide activation inhibitor of ERK was also used. Our results indicated a decrease in mitotic spindle microtubules and an absence of cells in most of the M-phase stages. GSK3â and PKCæ enrichment were however not inhibited at the centrosomes. Taken together, the kinases GSK3â and PKCæ may not function as a part of the MAPK pathway to regulate the mitotic spindle.
ContributorsChakravadhanula, Madhavi (Author) / Capco, David G. (Thesis advisor) / Chandler, Douglas (Committee member) / Clark-Curtiss, Josephine (Committee member) / Newfeld, Stuart (Committee member) / Arizona State University (Publisher)
Created2012
Description
Studies of ancient pathogens are moving beyond simple confirmatory analysis of diseased bone; bioarchaeologists and ancient geneticists are posing nuanced questions and utilizing novel methods capable of confronting the debates surrounding pathogen origins and evolution, and the relationships between humans and disease in the past. This dissertation examines two ancient human diseases through molecular and bioarchaeological lines of evidence, relying on techniques in paleogenetics and phylogenetics to detect, isolate, sequence and analyze ancient and modern pathogen DNA within an evolutionary framework. Specifically this research addresses outstanding issues regarding a) the evolution, origin and phylogenetic placement of the pathogen causing skeletal tuberculosis in New World prior to European contact, and b) the phylogeny and origins of the parasite causing the human leishmaniasis disease complex. An additional chapter presents a review of the major technological and theoretical advances in ancient pathogen genomics to frame the contributions of this work within a rapidly developing field. This overview emphasizes that understanding the evolution of human disease is critical to contextualizing relationships between humans and pathogens, and the epidemiological shifts observed both in the past and in the present era of (re)emerging infectious diseases. These questions continue to be at the forefront of not only pathogen research, but also
bioarchaeological and paleopathological scholarship.
bioarchaeological and paleopathological scholarship.
ContributorsHarkins, Kelly M (Author) / Buikstra, Jane E. (Thesis advisor) / Stone, Anne C (Thesis advisor) / Knudson, Kelly (Committee member) / Kumar, Sudhir (Committee member) / Krause, Johannes (Committee member) / Arizona State University (Publisher)
Created2014
Description
Proteins are a fundamental unit in biology. Although proteins have been extensively studied, there is still much to investigate. The mechanism by which proteins fold into their native state, how evolution shapes structural dynamics, and the dynamic mechanisms of many diseases are not well understood. In this thesis, protein folding is explored using a multi-scale modeling method including (i) geometric constraint based simulations that efficiently search for native like topologies and (ii) reservoir replica exchange molecular dynamics, which identify the low free energy structures and refines these structures toward the native conformation. A test set of eight proteins and three ancestral steroid receptor proteins are folded to 2.7Å all-atom RMSD from their experimental crystal structures. Protein evolution and disease associated mutations (DAMs) are most commonly studied by in silico multiple sequence alignment methods. Here, however, the structural dynamics are incorporated to give insight into the evolution of three ancestral proteins and the mechanism of several diseases in human ferritin protein. The differences in conformational dynamics of these evolutionary related, functionally diverged ancestral steroid receptor proteins are investigated by obtaining the most collective motion through essential dynamics. Strikingly, this analysis shows that evolutionary diverged proteins of the same family do not share the same dynamic subspace. Rather, those sharing the same function are simultaneously clustered together and distant from those functionally diverged homologs. This dynamics analysis also identifies 77% of mutations (functional and permissive) necessary to evolve new function. In silico methods for prediction of DAMs rely on differences in evolution rate due to purifying selection and therefore the accuracy of DAM prediction decreases at fast and slow evolvable sites. Here, we investigate structural dynamics through computing the contribution of each residue to the biologically relevant fluctuations and from this define a metric: the dynamic stability index (DSI). Using DSI we study the mechanism for three diseases observed in the human ferritin protein. The T30I and R40G DAMs show a loss of dynamic stability at the C-terminus helix and nearby regulatory loop, agreeing with experimental results implicating the same regulatory loop as a cause in cataracts syndrome.
ContributorsGlembo, Tyler J (Author) / Ozkan, Sefika B (Thesis advisor) / Thorpe, Michael F (Committee member) / Ros, Robert (Committee member) / Kumar, Sudhir (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-task learning (MTL) aims to improve the generalization performance (of the resulting classifiers) by learning multiple related tasks simultaneously. Specifically, MTL exploits the intrinsic task relatedness, based on which the informative domain knowledge from each task can be shared across multiple tasks and thus facilitate the individual task learning. It is particularly desirable to share the domain knowledge (among the tasks) when there are a number of related tasks but only limited training data is available for each task. Modeling the relationship of multiple tasks is critical to the generalization performance of the MTL algorithms. In this dissertation, I propose a series of MTL approaches which assume that multiple tasks are intrinsically related via a shared low-dimensional feature space. The proposed MTL approaches are developed to deal with different scenarios and settings; they are respectively formulated as mathematical optimization problems of minimizing the empirical loss regularized by different structures. For all proposed MTL formulations, I develop the associated optimization algorithms to find their globally optimal solution efficiently. I also conduct theoretical analysis for certain MTL approaches by deriving the globally optimal solution recovery condition and the performance bound. To demonstrate the practical performance, I apply the proposed MTL approaches on different real-world applications: (1) Automated annotation of the Drosophila gene expression pattern images; (2) Categorization of the Yahoo web pages. Our experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.
ContributorsChen, Jianhui (Author) / Ye, Jieping (Thesis advisor) / Kumar, Sudhir (Committee member) / Liu, Huan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2011
Description
We propose a novel solution to prevent cancer by developing a prophylactic cancer. Several sources of antigens for cancer vaccines have been published. Among these, antigens that contain a frame-shift (FS) peptide or viral peptide are quite attractive for a variety of reasons. FS sequences, from either mistake in RNA processing or in genomic DNA, may lead to generation of neo-peptides that are foreign to the immune system. Viral peptides presumably would originate from exogenous but integrated viral nucleic acid sequences. Both are non-self, therefore lessen concerns about development of autoimmunity. I have developed a bioinformatical approach to identify these aberrant transcripts in the cancer transcriptome. Their suitability for use in a vaccine is evaluated by establishing their frequencies and predicting possible epitopes along with their population coverage according to the prevalence of major histocompatibility complex (MHC) types. Viral transcripts and transcripts with FS mutations from gene fusion, insertion/deletion at coding microsatellite DNA, and alternative splicing were identified in NCBI Expressed Sequence Tag (EST) database. 48 FS chimeric transcripts were validated in 50 breast cell lines and 68 primary breast tumor samples with their frequencies from 4% to 98% by RT-PCR and sequencing confirmation. These 48 FS peptides, if translated and presented, could be used to protect more than 90% of the population in Northern America based on the prediction of epitopes derived from them. Furthermore, we synthesized 150 peptides that correspond to FS and viral peptides that we predicted would exist in tumor patients and we tested over 200 different cancer patient sera. We found a number of serological reactive peptide sequences in cancer patients that had little to no reactivity in healthy controls; strong support for the strength of our bioinformatic approach. This study describes a process used to identify aberrant transcripts that lead to a new source of antigens that can be tested and used in a prophylactic cancer vaccine. The vast amount of transcriptome data of various cancers from the Cancer Genome Atlas (TCGA) project will enhance our ability to further select better cancer antigen candidates.
ContributorsLee, HoJoon (Author) / Johnston, Stephen A. (Thesis advisor) / Kumar, Sudhir (Committee member) / Miller, Laurence (Committee member) / Stafford, Phillip (Committee member) / Sykes, Kathryn (Committee member) / Arizona State University (Publisher)
Created2012
Description
One of the fundamental questions in molecular biology is how genes and the control of their expression give rise to so many diverse phenotypes in nature. The mRNA molecule plays a key role in this process as it directs the spatial and temporal expression of genetic information contained in the DNA molecule to precisely instruct biological processes in living organisms. The region located between the STOP codon and the poly(A)-tail of the mature mRNA, known as the 3′Untranslated Region (3′UTR), is a key modulator of these activities. It contains numerous sequence elements that are targeted by trans-acting factors that dose gene expression, including the repressive small non-coding RNAs, called microRNAs.
Recent transcriptome data from yeast, worm, plants, and humans has shown that alternative polyadenylation (APA), a mechanism that enables expression of multiple 3′UTR isoforms for the same gene, is widespread in eukaryotic organisms. It is still poorly understood why metazoans require multiple 3′UTRs for the same gene, but accumulating evidence suggests that APA is largely regulated at a tissue-specific level. APA may direct combinatorial variation between cis-elements and microRNAs, perhaps to regulate gene expression in a tissue-specific manner. Apart from a few single gene anecdotes, this idea has not been systematically explored.
This dissertation research employs a systems biology approach to study the somatic tissue dynamics of APA and its impact on microRNA targeting networks in the small nematode C. elegans. In the first aim, tools were developed and applied to isolate and sequence mRNA from worm intestine and muscle tissues, which revealed pervasive tissue-specific APA correlated with microRNA regulation. The second aim provides genetic evidence that two worm genes use APA to escape repression by microRNAs in the body muscle. Finally, in aim three, mRNA from five additional somatic worm tissues was sequenced and their 3′ends mapped, allowing for an integrative study of APA and microRNA targeting dynamics in worms. Together, this work provides evidence that APA is a pervasive mechanism operating in somatic tissues of C. elegans with the potential to significantly rearrange their microRNA regulatory networks and precisely dose their gene expression.
Recent transcriptome data from yeast, worm, plants, and humans has shown that alternative polyadenylation (APA), a mechanism that enables expression of multiple 3′UTR isoforms for the same gene, is widespread in eukaryotic organisms. It is still poorly understood why metazoans require multiple 3′UTRs for the same gene, but accumulating evidence suggests that APA is largely regulated at a tissue-specific level. APA may direct combinatorial variation between cis-elements and microRNAs, perhaps to regulate gene expression in a tissue-specific manner. Apart from a few single gene anecdotes, this idea has not been systematically explored.
This dissertation research employs a systems biology approach to study the somatic tissue dynamics of APA and its impact on microRNA targeting networks in the small nematode C. elegans. In the first aim, tools were developed and applied to isolate and sequence mRNA from worm intestine and muscle tissues, which revealed pervasive tissue-specific APA correlated with microRNA regulation. The second aim provides genetic evidence that two worm genes use APA to escape repression by microRNAs in the body muscle. Finally, in aim three, mRNA from five additional somatic worm tissues was sequenced and their 3′ends mapped, allowing for an integrative study of APA and microRNA targeting dynamics in worms. Together, this work provides evidence that APA is a pervasive mechanism operating in somatic tissues of C. elegans with the potential to significantly rearrange their microRNA regulatory networks and precisely dose their gene expression.
ContributorsBlazie, Stephen M (Author) / Mangone, Marco (Thesis advisor) / LaBaer, Josh (Committee member) / Lake, Doug (Committee member) / Newfeld, Stuart (Committee member) / Arizona State University (Publisher)
Created2016
Description
Systems biology studies complex biological systems. It is an interdisciplinary field, with biologists working with non-biologists such as computer scientists, engineers, chemists, and mathematicians to address research problems applying systems’ perspectives. How these different researchers and their disciplines differently contributed to the advancement of this field over time is a question worth examining. Did systems biology become a systems-oriented science or a biology-oriented science from 1992 to 2013?
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
ContributorsZou, Yawen (Author) / Laubichler, Manfred (Thesis advisor) / Maienschein, Jane (Thesis advisor) / Creath, Richard (Committee member) / Ellison, Karin (Committee member) / Newfeld, Stuart (Committee member) / Arizona State University (Publisher)
Created2016