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Genome analysis with the conditional multinomial distribution profile.

ABSTRACT: The focus of the research is on the analysis of genome sequences. Based on the inter-nucleotide distance sequence, we propose the conditional multinomial distribution profile for the complete genomic sequence. These profiles can be used to define a very simple, computationally efficient, alignment-free, distance measure that reflects the evolutionary relationships between genomic sequences. We use this distance measure to classify chromosomes according to species of origin, to build the phylogenetic tree of 24 complete genome sequences of coronaviruses. Our results demonstrate the new method is powerful and efficient.

SUBMITTER: Chang G

PROVIDER: S-EPMC7094119 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Genome analysis with the conditional multinomial distribution profile.

Chang Guisong G Wang Tianming T

Journal of theoretical biology 20101201 1

The focus of the research is on the analysis of genome sequences. Based on the inter-nucleotide distance sequence, we propose the conditional multinomial distribution profile for the complete genomic sequence. These profiles can be used to define a very simple, computationally efficient, alignment-free, distance measure that reflects the evolutionary relationships between genomic sequences. We use this distance measure to classify chromosomes according to species of origin, to build the phylogen ...[more]

PMID: 21129383

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Project description:BackgroundUndernutrition is an important public health indicator for monitoring nutritional status and survival. In spite of its importance, undernutrition is a significant problem health problem in many East African communities. The aim of this study was to identify factors associated with childhood undernutrition in three disadvantaged East African Districts.MethodsWe examined data for 9270 children aged 0-59 months using cross-sectional survey from Gicumbi District in Rwanda, Kitgum District in Uganda and Kilindi District in Tanzania. We considered the level of undernutrition (stunting, wasting and underweight) as the outcome variables with four ordinal categories (severely undernourished, moderately undernourished, mildly undernourished, and nourished). Generalized linear latent and mixed models (GLLAMM) with the mlogit link and binomial family that adjusted for clustering and sampling weights were used to identify factors associated with undernutrition among children aged 0-59 months in three disadvantaged East African Districts.ResultsAfter adjusting for potential confounding factors, the odds of a child being stunted were higher in Gicumbi District in Rwanda while the odds of a child being wasted and underweight were higher in Kitgum District in Uganda. Having diarrhoea two weeks prior to the survey was significantly associated with severe undernutrition. Wealth index (least poor household), increasing child's age, sex of the child (male) and unavailability of water all year were reported to be associated with moderate or severe stunting/wasting. Children of women who did not attend monthly child growth monitoring sessions and children who had Acute Respiratory Infection (ARI) symptoms were significantly associated with moderate or severe underweight.ConclusionsFindings from our study indicated that having diarrhoea, having ARI, not having water availability all year and not attending monthly child growth monitoring sessions were associated with undernutrition among children aged 0-59 months. Interventions aimed at improving undernutrition in these disadvantaged communities should target all children especially those children from households with poor sanitation practices.

Dataset Information

Genome analysis with the conditional multinomial distribution profile.

Publications

Genome analysis with the conditional multinomial distribution profile.

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