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Biomedical subjects

Ron Y Pinter

Publications and source records attributed to Ron Y Pinter.

7 recordsLinked to original sources

An integrative method for accurate comparative genome mapping.

We present MAGIC, an integrative and accurate method for comparative genome mapping. Our method consists of two phases: preprocessing for identifying "maximal similar segments," and mapping for clustering and classifying these segments. MAGIC's main novelty lies in its biologically intuitive clustering approach, which aims towards both calculating reorder-free segments and identifying orthologous segments. In the process, MAGIC efficiently handles ambiguities resulting from duplications that occurred before the speciation of the considered organisms from their most recent common ancestor. We demonstrate both MAGIC's robustness and scalability: the former is asserted with respect to its initial input and with respect to its parameters' values. The latter is asserted by applying MAGIC to distantly related organisms and to large genomes. We compare MAGIC to other comparative mapping methods and provide detailed analysis of the differences between them. Our improvements allow a comprehensive study of the diversity of genetic repertoires resulting from large-scale mutations, such as indels and duplications, including explicitly transposable and phagic elements. The strength of our method is demonstrated by detailed statistics computed for each type of these large-scale mutations. MAGIC enabled us to conduct a comprehensive analysis of the different forces shaping prokaryotic genomes from different clades, and to quantify the importance of novel gene content introduced by horizontal gene transfer relative to gene duplication in bacterial genome evolution. We use these results to investigate the breakpoint distribution in several prokaryotic genomes.

Algorithms↗

On the repeat-annotated phylogenetic tree reconstruction problem.

A new problem in phylogenetic inference is presented, based on recent biological findings indicating a strong association between reversals (i.e., inversions) and repeats. These biological findings are formalized here in a new mathematical model, called repeat-annotated phylogenetic trees (RAPT). We show that, under RAPT, the evolutionary process--including both the tree-topology as well as internal node genome orders--is uniquely determined, a property that is of major significance both in theory and in practice. Furthermore, the repeats are employed to provide linear-time algorithms for reconstructing both the genomic orders and the phylogeny, which are NP-hard problems under the classical model of sorting by reversals (SBR).

Algorithms↗

A high-throughput approach for associating MicroRNAs with their activity conditions.

Plant microRNAs (miRNAs) are short RNA sequences that bind to target mRNAs and change their expression levels by redirecting their stabilities and marking them for cleavage. In Arabidopsis thaliana, microRNAs have been shown to regulate development and are believed to impact expression both under various conditions, such as stress and stimuli, as well as in specific tissue types. We present a high throughput approach for associating between microRNAs and conditions in which they act, using novel statistical and algorithmic techniques. Our new tool, miRNAXpress, at first computes a (binary) matrix T denoting the potential targets of microRNAs. Then, using T and an additional predefined matrix X indicating expression of genes under various conditions, it produces a new matrix that predicts associations between microRNAs and the conditions in which they act. Thus, the program comprises two main modules that work in tandem to compute the desired output. The first is an efficient target prediction engine that predicts mRNA targets of query microRNAs by evaluating the optimal duplex that could be formed between the two: given a short query RNA, a long target RNA, and a predefined energy cut-off threshold, the program finds and reports all putative binding sites of the query RNA in the target RNA with hybridization energy bounded by the predefined threshold. The second module realizes an association operation that is computed by a method which relies on an efficient t-test to compute the associations. The calculation of the matrix of microRNAs and their potential targets is the computationally intensive part of the work done by miRNAXpress, and therefore an efficient algorithm for this portion facilitates the entire process. Thus, the target prediction engine is based on an efficient approximate hybridization search algorithm whose efficiency is the result of utilizing the sparsity of the search space without sacrificing the optimality of the results. The time complexity of this algorithm is almost linear in the size of a sparse set of locations where base-pairs are stacked at a height of three or more. Thus miRNAXpress is a novel tool for associating between microRNAs and the conditions in which they act. We employed it to conduct a study, using the plant Arabidopsis thaliana as our model organism. By applying miRNAXpress to 98 microRNAs and 380 conditions, some biologically interesting and statistically strong relations were discovered. For example, mir159C activity is possibly a factor in the misresponse of nph4 mutants to phototropic stimulations.

Arabidopsis↗

Computer modelling of antifolate inhibition of folate metabolism using hybrid functional petri nets.

Antifolates are used in the treatment of various human malignancies and exert their cytotoxic activity by inhibiting folate-dependent enzymes resulting in disruption of DNA synthesis and cell death. Here we devised a computerized hybrid functional petri nets (HFPN) modelling of folate metabolism under physiological and antifolate inhibitory conditions. This HFPN modelling proved valid as a good agreement was found between the simulated steady-state concentrations of various reduced folates and those published for cell extracts; consistently, the simulation derived total folate pool size (11.3 microM) was identical to that published for cell extracts. In silico experiments were conducted to characterize the inhibitory profile of four distinct antifolates including methotrexate (MTX), tomudex, and LY309887, which inhibit dihydrofolate reductase (DHFR), thymidylate synthase (TS) and glycineamide ribonucleotide transformylase (GARTFase), respectively, as well as pemetrexed which has the capacity to inhibit all three enzymes. In order to assess the inhibitory activity of antifolates on purines and pyrimidines, the biosynthesis rates of IMP (20.53 microM/min) and dTMP (23.8 microM/min) were first simulated. Whereas the biochemical inhibitory profile of MTX was characterized by increased dihydrofolate and decreased tetrahydrofolate (THF) concentrations, the remaining antifolates did not decrease THF levels. Furthermore, MTX was 766- and 10-fold more potent in decreasing the production rates of IMP and dTMP, respectively, than pemetrexed. LY309887 indirectly decreased the rate of dTMP production by reducing the levels of 5-CH2-THF, a folate cofactor for TS. Surprisingly, pemetrexed failed to inhibit DHFR even at high concentrations. This HFPN-based simulation offers an inexpensive, user-friendly, rapid and reliable means of pre-clinical evaluation of the inhibitory profiles of antifolates.

Antimetabolites, Antineoplastic↗

Alignment of metabolic pathways.

MOTIVATION: Several genome-scale efforts are underway to reconstruct metabolic networks for a variety of organisms. As the resulting data accumulates, the need for analysis tools increases. A notable requirement is a pathway alignment finder that enables both the detection of conserved metabolic pathways among different species as well as divergent metabolic pathways within a species. When comparing two pathways, the tool should be powerful enough to take into account both the pathway topology as well as the nodes' labels (e.g. the enzymes they denote), and allow flexibility by matching similar--rather than identical--pathways. RESULTS: MetaPathwayHunter is a pathway alignment tool that, given a query pathway and a collection of pathways, finds and reports all approximate occurrences of the query in the collection, ranked by similarity and statistical significance. It is based on a novel, efficient graph matching algorithm that extends the functionality of known techniques. The program also supports a visualization interface with which the alignment of two homologous pathways can be graphically displayed. We employed this tool to study the similarities and differences in the metabolic networks of the bacterium Escherichia coli and the yeast Saccharomyces cerevisiae, as represented in highly curated databases. We reaffirmed that most known metabolic pathways common to both the species are conserved. Furthermore, we discovered a few intriguing relationships between pathways that provide insight into the evolution of metabolic pathways. We conclude with a description of biologically meaningful meta-queries, demonstrating the power and flexibility of our new tool in the analysis of metabolic pathways.

Animals↗

Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction.

Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of protein-protein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

Amino Acid Motifs↗

Genomic sorting with length-weighted reversals.

Current algorithmic studies of genome rearrangement ignore the length of reversals (or inversions); rather, they only count their number. We introduce a new cost model in which the lengths of the reversed sequences play a role, allowing more flexibility in accounting for mutation phenomena. Our focus is on sorting unsigned (unoriented) permutations by reversals; since this problem remains difficult (NP-hard) in our new model, the best we can hope for are approximation results. We propose an efficient, novel algorithm that takes (a monotonic function f of) length into account as an optimization criterion and study its properties. Our results include an upper bound of O(fn lg2n) for any additive cost measure f on the cost of sorting any n-element permutation, and a guaranteed approximation ratio of O(lg2n) times optimal for sorting a given permutation. Our work poses some interesting questions to both biologists and computer scientists and suggests some new bioinformatic insights that are currently being studied.

Algorithms↗