I. Saira Mian

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Hidden Markov Models (HMMs) are applied to the problems of statistical modeling, database searching and multiple sequence alignment of protein families and protein domains. These methods are demonstrated on the globin family, the protein kinase catalytic domain, and the EF-hand calcium binding motif. In each case the parameters of an HMM are estimated from(More)
We present a method for condensing the information in multiple alignments of proteins into a mixture of Dirichlet densities over amino acid distributions. Dirichlet mixture densities are designed to be combined with observed amino acid frequencies to form estimates of expected amino acid probabilities at each position in a profile, hidden Markov model or(More)
Stochastic context-free grammars (SCFGs) are applied to the problems of folding, aligning and modeling families of tRNA sequences. SCFGs capture the sequences' common primary and secondary structure and generalize the hidden Markov models (HMMs) used in related work on protein and DNA. Results show that after having been trained on as few as 20 tRNA(More)
Mice deficient in Klotho gene expression exhibit a syndrome resembling premature human aging. To determine whether variation in the human KLOTHO locus contributes to survival, we applied two newly characterized polymorphic microsatellite markers flanking the gene in a population-based association study. In a cohort chosen for its homogeneity, Bohemian(More)
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein family or the columns of a multiple alignment of that family is introduced. This method uses Dirichlet mixture densities as priors over amino acid distributions. These mixture densities are determined from examination of previously(More)
Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring.(More)
Molecular profiling studies can generate abundance measurements for thousands of transcripts, proteins, metabolites, or other species in, for example, normal and tumor tissue samples. Treating such measurements as features and the samples as labeled data points, sparse hyperplanes provide a statistical methodology for classifying data points into one of two(More)
Introduction A problem in developmental biology that continues to take center stage is how higher organisms generate diverse tissues and organs given the same cellular genotype. In cell and tumor biology, the key question is not the production of form, but its preservation: how do tissues and organs maintain homeostasis, and how do cells within tissues lose(More)
The International Registry of Werner syndrome (www.wernersyndrome.org) has been providing molecular diagnosis of the Werner syndrome (WS) for the past decade. The present communication summarizes, from among 99 WS subjects, the spectrum of 50 distinct mutations discovered by our group and by others since the WRN gene (also called RECQL2 or REQ3) was first(More)