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Bud Mishra

Publications and source records attributed to Bud Mishra.

11 recordsLinked to original sources
PubMed2006

Quantitative analysis of germline mitosis in adult C. elegans.

Certain aspects of the distal gonad of C. elegans are comparable to niche/stem cell systems in other organisms. The distal tip cell (DTC) caps a blind-ended tube; only the distal germ cells maintain proliferation in response to signaling from the DTC via the GLP-1/Notch signaling pathway in the germ line. Fruitful comparison between this system and other stem cell systems is limited by a lack of basic information regarding germ cell division behavior in C. elegans. Here, we explore the spatial pattern of cell division frequency in the adult C. elegans germ line relative to distance from the distal tip. We mapped the positions of actively dividing germline nuclei in over 600 fixed gonad preparations including the wild type and a gain-of-function ligand-responsive GLP-1 receptor mutant with an extended mitotic zone. One particularly surprising observation from these data is that the frequency of cell divisions is lower in distal-most cells-cells that directly contact the distal tip cell body-relative to cells further proximal, a difference that persists in the gain-of-function GLP-1 mutant. These results suggest that cell division frequency in the distal-most cells may be suppressed or otherwise controlled in a complex manner. Further, our data suggest that the presence of an active cell division influences the probability of observing simultaneous cell divisions in the same gonad arm, and that simultaneous divisions tend to cluster spatially. We speculate that this system behaves similarly to niche/stem cell/transit amplifying cell systems in other organisms.

Animals↗
PubMed2006

Interpreter of maladies: redescription mining applied to biomedical data analysis.

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Algorithms↗
PubMed2005

A coherent framework for multiresolution analysis of biological networks with "memory": Ras pathway, cell cycle, and immune system.

Various biological processes exhibit characteristics that vary dramatically in response to different input conditions or changes in the history of the process itself. One of the examples studied here, the Ras-PKC-mitogen-activated protein kinase (MAPK) bistable pathway, follows two distinct dynamics (modes) depending on duration and strength of EGF stimulus. Similar examples are found in the behavior of the cell cycle and the immune system. A classification methodology, based on time-frequency analysis, was developed and tested on these systems to understand global behavior of biological processes. Contrary to most traditionally used statistical and spectral methods, our approach captures complex functional relations between parts of the systems in a simple way. The resulting algorithms are capable of analyzing and classifying sets of time-series data obtained from in vivo or in vitro experiments, or in silico simulation of biological processes. The method was found to be considerably stable under stochastic noise perturbation and, therefore, suitable for the analysis of real experimental data.

Algorithms↗
PubMed2005

Quantifying the mechanisms for segmental duplications in mammalian genomes by statistical analysis and modeling.

A large number of the segmental duplications in mammalian genomes have been cataloged by genome-wide sequence analyses. The molecular mechanisms involved in these duplications mostly remain a matter of speculation. To uncover, test, and further quantify the hypotheses on the mechanisms for the recent duplications in the mammalian genomes, we have performed a series of statistical analyses on the sequences flanking the duplicated segments and proposed a dynamic model for the duplication process. The model, when applied to the human duplication data, indicates that approximately 30% of the recent human segmental duplications were caused by a recombination-like mechanism, among which 12% were mediated by the most recently active repeat, Alu. But a significant proportion of the duplications are caused by some mechanism independent of the repeat distribution. A less sure but similar picture is found in the rodent genomes. A further analysis on the physical features of the flanking sequences suggests that one of the uncharacterized duplication mechanisms shared by the mammalian genomes is surprisingly well correlated with the physical instability in the DNA sequences.

Animals↗
PubMed2004

A versatile statistical analysis algorithm to detect genome copy number variation.

We have developed a versatile statistical analysis algorithm for the detection of genomic aberrations in human cancer cell lines. The algorithm analyzes genomic data obtained from a variety of array technologies, such as oligonucleotide array, bacterial artificial chromosome array, or array-based comparative genomic hybridization, that operate by hybridizing with genomic material obtained from cancer and normal cells and allow detection of regions of the genome with altered copy number. The number of probes (i.e., resolution), the amount of uncharacterized noise per probe, and the severity of chromosomal aberrations per chromosomal region may vary with the underlying technology, biological sample, and sample preparation. Constrained by these uncertainties, our algorithm aims at robustness by using a priorless maximum a posteriori estimator and at efficiency by a dynamic programming implementation. We illustrate these characteristics of our algorithm by applying it to data obtained from representational oligonucleotide microarray analysis and array-based comparative genomic hybridization technology as well as to synthetic data obtained from an artificial model whose properties can be varied computationally. The algorithm can combine data from multiple sources and thus facilitate the discovery of genes and markers important in cancer, as well as the discovery of loci important in inherited genetic disease.

Algorithms↗
PubMed2004

Distribution of short paired duplications in mammalian genomes.

Mammalian genomes are densely populated with long duplicated sequences. In this paper, we demonstrate the existence of doublets, short duplications between 25 and 100 bp, distinct from previously described repeats. Each doublet is a pair of exact matches, separated by some distance. The distribution of these intermatch distances is strikingly nonrandom. An unexpectedly high number of doublets have matches either within 100 bp (adjacent) or at distances tightly concentrated approximately 1,000 bp apart (nearby). We focus our study on these proximate doublets. First, they tend to have both matches on the same strand. By comparing nearby doublets shared in human and chimpanzee, we can also see that these doublets seem to arise by an insertion event that produces a copy without markedly affecting the surrounding sequence. Most doublets in humans are shared with chimpanzee, but many new pairs arose after the divergence of the species. Doublets found in human but not chimpanzee are most often composed of almost tandem matches, whereas older doublets (found in both species) are more likely to have matches spaced by approximately 1 kb, indicating that the nearly tandem doublets may be more dynamic. The spacing of doublets is highly conserved. So far, we have found clearly recognizable doublets in the following genomes: Homo sapiens, Mus musculus, Arabidopsis thaliana, and Caenorhabditis elegans, indicating that the mechanism generating these doublets is widespread. A mechanism that generates short local duplications while conserving polarity could have a profound impact on the evolution of regulatory and protein-coding sequences.

Animals↗
PubMed2003

Shrinkage-based similarity metric for cluster analysis of microarray data.

The current standard correlation coefficient used in the analysis of microarray data was introduced by M. B. Eisen, P. T. Spellman, P. O. Brown, and D. Botstein [(1998) Proc. Natl. Acad. Sci. USA 95, 14863-14868]. Its formulation is rather arbitrary. We give a mathematically rigorous correlation coefficient of two data vectors based on James-Stein shrinkage estimators. We use the assumptions described by Eisen et al., also using the fact that the data can be treated as transformed into normal distributions. While Eisen et al. use zero as an estimator for the expression vector mean mu, we start with the assumption that for each gene, mu is itself a zero-mean normal random variable [with a priori distribution N(0,tau 2)], and use Bayesian analysis to obtain a posteriori distribution of mu in terms of the data. The shrunk estimator for mu differs from the mean of the data vectors and ultimately leads to a statistically robust estimator for correlation coefficients. To evaluate the effectiveness of shrinkage, we conducted in silico experiments and also compared similarity metrics on a biological example by using the data set from Eisen et al. For the latter, we classified genes involved in the regulation of yeast cell-cycle functions by computing clusters based on various definitions of correlation coefficients and contrasting them against clusters based on the activators known in the literature. The estimated false positives and false negatives from this study indicate that using the shrinkage metric improves the accuracy of the analysis.

Algorithms↗
PubMed2003

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Animals↗
PubMed2003

Model building and model checking for biochemical processes.

A central claim of computational systems biology is that, by drawing on mathematical approaches developed in the context of dynamic systems, kinetic analysis, computational theory and logic, it is possible to create powerful simulation, analysis, and reasoning tools for working biologists to decipher existing data, devise new experiments, and ultimately to understand functional properties of genomes, proteomes, cells, organs, and organisms. In this article, a novel computational tool is described that achieves many of the goals of this new discipline. The novelty of this system involves an automaton-based semantics of the temporal evolution of complex biochemical reactions starting from the representation given as a set of differential equations. The related tools also provide ability to qualitatively reason about the systems using a propositional temporal logic that can express an ordered sequence of events succinctly and unambiguously. The implementation of mathematical and computational models in the Simpathica and XSSYS systems is described briefly. Several example applications of these systems to cellular and biochemical processes are presented: the two most prominent are Leibler et al.'s repressilator (an artificial synthesized oscillatory network), and Curto- Voit-Sorribas-Cascante's purine metabolism reaction model.

Biochemical Phenomena↗
PubMedDate not supplied

Validation of S. pombe sequence assembly by microarray hybridization.

We describe a method to make physical maps of genomes using correlative hybridization patterns of probes to random pools of BACs. We derive thereby an estimated distance between probes, and then use this estimated distance to order probes. To test the method, we used BAC libraries from Schizzosaccharomyces pombe. We compared our data to the known sequence assembly, in order to assess accuracy. We demonstrate a small number of significant discrepancies between our method and the map derived by sequence assembly. Some of these discrepancies may arise because genome order within a population is not stable; imposing a linear order on a population may not be biologically meaningful.

Algorithms↗