Matrix Decomposition Methods for Data Mining : Computational Complexity and Algorithms

Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays

This thesis presents a highly sensitive genome wide search method for recessive mutations. The method is suitable for distantly related samples that are divided into phenotype positives and negatives. High throughput genotype arrays are used to identify and compare homozygous regions between the cohorts. The method is demonstrated by comparing colorectal cancer patients against unaffected references. The objective is to find homozygous regions and alleles that are more common in cancer patients. We have designed and implemented software tools to automate the data analysis from genotypes to lists of candidate genes and to their properties. The programs have been designed in respect to a pipeline architecture that allows their integration to other programs such as biological databases and copy number analysis tools. The integration of the tools is crucial as the genome wide analysis of the cohort differences produces many candidate regions not related to the studied phenotype. CohortComparator is a genotype comparison tool that detects homozygous regions and compares their loci and allele constitutions between two sets of samples. The data is visualised in chromosome specific graphs illustrating the homozygous regions and alleles of each sample. The genomic regions that may harbour recessive mutations are emphasised with different colours and a scoring scheme is given for these regions. The detection of homozygous regions, cohort comparisons and result annotations are all subjected to presumptions many of which have been parameterized in our programs. The effect of these parameters and the suitable scope of the methods have been evaluated. Samples with different resolutions can be balanced with the genotype estimates of their haplotypes and they can be used within the same study.

Computational analyses of the catalytic and heparin-binding sites and their interactions with glycosaminoglycans in glycoside hydrolase family 79 endo-d-glucuronidase (heparanase)

Mammalian heparanase is an endo-β-glucuronidase associated with cell invasion in cancer metastasis, angiogenesis and inflammation. Heparanase cleaves heparan sulfate proteoglycans in the extracellular matrix and basement membrane, releasing heparin/heparan sulfate oligosaccharides of appreciable size. This in turn causes the release of growth factors, which accelerate tumor growth and metastasis. Heparanase has two glycosaminoglycan-binding domains; however, no three-dimensional structure information is available for human heparanase that can provide insights into how the two domains interact to degrade heparin fragments. We have constructed a new homology model of heparanase that takes into account the most recent structural and bioinformatics data available. Heparin analogs and glycosaminoglycan mimetics were computationally docked into the active site with energetically stable ring conformations and their interaction energies were compared. The resulting docked structures were used to propose a model for substrates and conformer selectivity based on the dimensions of the active site. The docking of substrates and inhibitors indicates the existence of a large binding site extending at least two saccharide units beyond the cleavage site (toward the nonreducing end) and at least three saccharides toward the reducing end (toward heparin-binding site 2). The docking of substrates suggests that heparanase recognizes the N-sulfated and O-sulfated glucosamines at subsite +1 and glucuronic acid at the cleavage site, whereas in the absence of 6-O-sulfation in glucosamine, glucuronic acid is docked at subsite +2. These findings will help us to focus on the rational design of heparanase-inhibiting molecules for anticancer drug development by targeting the two heparin/heparan sulfate recognition domains.

Computational methods for the prediction of the structure and interactions of coiled-coil peptides

The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.

Situated interpretation in computational creativity

This paper describes, formalizes and implements an approach to computational creativity based on situated interpretation. The paper introduces the notions of framing and reframing of conceptual spaces based on empirical studies as the driver for this research. It uses concepts from situated cognition, and situated interpretation in particular, to be the basis of a formal model of the movement between conceptual spaces. This model is implemented using rules within interacting neural networks. This implementation demonstrates behaviour similar to that observed in studies of human designers.

Two highly unsymmetrical tetradentate (N3O) Schiff base copper(II) complexes: Template synthesis, structural characterization, magnetic and computational studies

Two new copper(II) complexes, [Cu-2(L-1)(2)](ClO4)(2) (1) and [Cu(L-2)(ClO4)] (2), of the highly unsymmetrical tetradentate (N3O) Schiff base ligands HL1 and HL2 (where HL1 = N-(2-hydroxyacetophenone)-bis-3-aminopropylamine and HL2 = N-(salicyldehydine)-bis-3-aminopropylamine) have been synthesised using a template method. Their single crystal X-ray structures show that in complex 1 two independent copper(II) centers are doubly bridged through sphenoxo-O atoms (O1A and O1B) of the two ligands and each copper atom is five-coordinated with a distorted square pyramidal geometry. The asymmetric unit of complex 2 consists of two crystallographically independe N-(salicylidene) bis(aminopropyl)amine-copper(II) molecules, A and B, with similar square pyramidal geometries. Cryomagnetic susceptibility measurements (5-300 K) on complex 1 reveal a distinct antiferromagnetic interaction with J=-23.6 cm(-1), which is substantiated by a DFT calculation (J=-27.6 cm(-1)) using the B3LYP functional. Complex 1, immobilized over highly ordered hexagonal mesoporous silica, shows moderate catalytic activity for the epoxidation of cyclohexene and styrene in the presence of TBHP as an oxidant.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Room temperature metathesis of aryl isocyanates and aromatic aldehydes catalyzed by group(IV) metal alkoxides: An experimental and computational study

Aromatic aldehydes and aryl isocyanates do not react at room temperature. However, we have shown for the first time that in the presence of catalytic amounts of group(IV) n-butoxide, they undergo metathesis at room temperature to produce imines with the extrusion of carbon dioxide. The mechanism of action has been investigated by a study of stoichiometric reactions. The insertion of aryl isocyanates into the metal n-butoxide occurs very rapidly. Reaction of the insertion product with the aldehyde is responsible for the metathesis. Among the n-butoxides of group(IV) metals, Ti((OBu)-Bu-n)(4) (8aTi) was found to be more efficient than Zr((OBu)-Bu-n)(4) (8aZr) and Hf((OBu)-Bu-n)(4) (8aHf) in carrying out metathesis. The surprisingly large difference in the metathetic activity of these alkoxides has been probed computationally using model complexes Ti(OMe)(4) (8bTi), Zr(OMe)(4) (8bZr) and Hf(OMe)(4) (8bHf) at the B3LYP/LANL2DZ level of theory. These studies indicate that the insertion product formed by Zr and Hf are extremely stable compared to that formed by Ti. This makes subsequent reaction of Zr and Hf complexes unfavorable.

Cucumber chloroplast trnL(CAA) gene: nucleotide sequence and in vivo expression analysis in etiolated cucumber seedlings treated with benzyladenine and light.

The nucleotide sequence of a 714 bp BamHI-EcoRI fragment of cucumber chloroplast DNA was determined. The fragment contained a gene for tRNA(Leu) together with its flanking regions. The trnL(CAA) gene sequence is about 99% in similarity to broad bean, cauliflower, maize, spinach and tobacco corresponding genes. The relative expression level of the gene was determined by Northern (tRNA) gel blot and Northern (total cellular RNA) slot-blot analyses using the trnL gene probe in 6-day old etiolated cucumber seedlings and the seedlings that had been kept in the dark (dark-grown), treated with benzyladenine (BA) and kept in the dark (BA-treated dark-grown), illuminated (light-grown), and treated with BA and illuminated (BA-treated light-grown), for additional 4, 8 or 12 hr. The trnL transcripts and tRNA(Leu) levels in BA-treated dark-grown seedlings were 5 and 3 times higher, respectively after 4 hr BA treatment, while in the BA treated light-grown seedlings the level of trnL transcripts was only 3 times higher and had no detectable effect on mature tRNA(Leu) when compared to the time-4 hr dark-grown seedlings. However, the level of mature tRNA(Leu) did not show marked changes in the light-grown seedlings, whereas the level of trnL transcripts increases 3 times after 8 hr illumination of dark-grown seedlings. These data indicate that both light and cytokinin can signal changes in plastid tRNA gene expression. The possible regulatory mechanisms for such changes are discussed.

Cucumber chloroplast trnL(CAA) gene: nucleotide sequence and in vivo expression analysis in etiolated cucumber seedlings treated with benzyladenine and light

The nucleotide sequence of a 714 bp BamHI-EcoRI fragment of cucumber chloroplast DNA was determined. The fragment contained a gene for tRNA(Leu) together with its flanking regions. The trnL(CAA) gene sequence is about 99% in similarity to broad bean, cauliflower, maize, spinach and tobacco corresponding genes. The relative expression level of the gene was determined by Northern (tRNA) gel blot and Northern (total cellular RNA) slot-blot analyses using the trnL gene probe in 6-day old etiolated cucumber seedlings and the seedlings that had been kept in the dark (dark-grown), treated with benzyladenine (BA) and kept in the dark (BA-treated dark-grown), illuminated (light-grown), and treated with BA and illuminated (BA- treated light-grown), for additional 4, 8 or 12 hr. The trnL transcripts and tRNA(Leu) levels in BA-treated dark-grown seedlings were 5 and 3 times higher, respectively after 4 hr BA treatment, while in the BA treated light-grown seedlings the level of trnL transcripts was only 3 times higher and had not detectable effect on mature tRNA(Leu) when compared to the time-4 hr dark-grown seedlings. However, the level of mature tRNA(Leu) did not show marked changes in the light-grown seedlings, whereas the level of trnL transcripts increases 3 times after 8 hr illumination of dark-grown seedlings. These date indicate that both light and cytokinin can signal changes in plastid tRNA gene expression. The possible regulatory mechanisms for such changes are discussed.

Design, Synthesis, and DNA Binding Properties of Photoisomerizable Azobenzene−Distamycin Conjugates: An Experimental and Computational Study

Here, we present the synthesis, photochemical, and DNA binding properties of three photoisomerizable azobenzene−distamycin conjugates in which two distamycin units were linked via electron-rich alkoxy or electron-withdrawing carboxamido moieties with the azobenzene core. Like parent distamycin A, these molecules also demonstrated AT-specific DNA binding. Duplex DNA binding abilities of these conjugates were found to depend upon the nature and length of the spacer, the location of protonatable residues, and the isomeric state of the conjugate. The changes in the duplex DNA binding efficiency of the individual conjugates in the dark and with their respective photoirradiated forms were examined by circular dichroism, thermal denaturation of DNA, and Hoechst displacement assay with poly[d(A-T).d(T-A)] DNA in 150 mM NaCl buffer. Computational structural analyses of the uncomplexed ligands using ab initio HF and MP2 theory and molecular docking studies involving the conjugates with duplex d[(GC(AT)10CG)]2 DNA were performed to rationalize the nature of binding of these conjugates.

Computational analysis of proteome of H5N1 avian influenza virus to define T cell epitopes with vaccine potential

The existing vaccines against influenza are based on the generation of neutralizing antibody primarily directed against surface proteins-hernagglutinin and neuraminidase. In this work, we have computationally defined conserved T cell epitopes of proteins of influenza virus H5N1 to help in the design of a vaccine with haplotype specificity for a target population. The peptides from the proteome of H5NI irus which are predicted to bind to different HLAs, do not show similarity with peptides of human proteorne and are also identified to be generated by proteolytic cleavage. These peptides could be made use of in the design of either a DNA vaccine or a subunit vaccine against V influenza. (c) 2007 Elsevier Ltd. All rights reserved.

Computational fluid dynamics simulations in aerosol and nucleation studies

Nucleation is the first step in the formation of a new phase inside a mother phase. Two main forms of nucleation can be distinguished. In homogeneous nucleation, the new phase is formed in a uniform substance. In heterogeneous nucleation, on the other hand, the new phase emerges on a pre-existing surface (nucleation site). Nucleation is the source of about 30% of all atmospheric aerosol which in turn has noticeable health effects and a significant impact on climate. Nucleation can be observed in the atmosphere, studied experimentally in the laboratory and is the subject of ongoing theoretical research. This thesis attempts to be a link between experiment and theory. By comparing simulation results to experimental data, the aim is to (i) better understand the experiments and (ii) determine where the theory needs improvement. Computational fluid dynamics (CFD) tools were used to simulate homogeneous onecomponent nucleation of n-alcohols in argon and helium as carrier gases, homogeneous nucleation in the water-sulfuric acid-system, and heterogeneous nucleation of water vapor on silver particles. In the nucleation of n-alcohols, vapor depletion, carrier gas effect and carrier gas pressure effect were evaluated, with a special focus on the pressure effect whose dependence on vapor and carrier gas properties could be specified. The investigation of nucleation in the water-sulfuric acid-system included a thorough analysis of the experimental setup, determining flow conditions, vapor losses, and nucleation zone. Experimental nucleation rates were compared to various theoretical approaches. We found that none of the considered theoretical descriptions of nucleation captured the role of water in the process at all relative humidities. Heterogeneous nucleation was studied in the activation of silver particles in a TSI 3785 particle counter which uses water as its working fluid. The role of the contact angle was investigated and the influence of incoming particle concentrations and homogeneous nucleation on counting efficiency determined.