Dataset Information

IntDb: A comprehensive database for classified introns of saccharomyces & human.

ABSTRACT: UNLABELLED:Introns (intra-genic) are non-coding regions of several eukaryotic genes. However, their role in regulation of transcription, embryonic development, stimulate gene (HEG) is apparent in recent years. Thus current research focuses on mutation in introns and their influence in causing various diseases. Though many available intron databases like YIDB, IDB, ExInt, GISSD, FUGOID, etc. discusses on various aspects of introns but none of them have classified the introns where identification of start intron is found to be important which mainly regulates the various activities of protein at gene level. This lead to an idea for development of "Intdb"; a database meant for classifying introns as start, middle and stop on the basis of position of specific consensus site. Information provided in IntDb is useful for gene prediction, determination of splicing sites and identification of diseases. In addition, the main focus is on violation of consensus rule and frequency of other deviations observed in classified introns. Further, GC content, length variations according to the biased residues and occurrence of consensus pattern to discover potential role of introns is also emphasized in IntDb. AVAILABILITY:The database is available for free at http://introndb.bicpu.edu.in/

SUBMITTER: Mohanty S

PROVIDER: S-EPMC3314878 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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IntDb: A comprehensive database for classified introns of saccharomyces & human.

Mohanty Subhalaxmi S Nizam Amouda A Biswal Monalisha M

Bioinformation 20120317 5

<h4>Unlabelled</h4>Introns (intra-genic) are non-coding regions of several eukaryotic genes. However, their role in regulation of transcription, embryonic development, stimulate gene (HEG) is apparent in recent years. Thus current research focuses on mutation in introns and their influence in causing various diseases. Though many available intron databases like YIDB, IDB, ExInt, GISSD, FUGOID, etc. discusses on various aspects of introns but none of them have classified the introns where identif ...[more]

PMID: 22493526

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Project description:This paper presents a comprehensive theory for the demographic analysis of populations in which individuals are classified by both age and stage. The earliest demographic models were age classified. Ecologists adopted methods developed by human demographers and used life tables to quantify survivorship and fertility of cohorts and the growth rates and structures of populations. Later, motivated by studies of plants and insects, matrix population models structured by size or stage were developed. The theory of these models has been extended to cover all the aspects of age-classified demography and more. It is a natural development to consider populations classified by both age and stage. A steady trickle of results has appeared since the 1960s, analyzing one or another aspect of age × stage-classified populations, in both ecology and human demography. Here, we use the vec-permutation formulation of multistate matrix population models to incorporate age- and stage-specific vital rates into demographic analysis. We present cohort results for the life table functions (survivorship, mortality, and fertility), the dynamics of intra-cohort selection, the statistics of longevity, the joint distribution of age and stage at death, and the statistics of life disparity. Combining transitions and fertility yields a complete set of population dynamic results, including population growth rates and structures, net reproductive rate, the statistics of lifetime reproduction, and measures of generation time. We present a complete analysis of a hypothetical model species, inspired by poecilogonous marine invertebrates that produce two kinds of larval offspring. Given the joint effects of age and stage, many familiar demographic results become multidimensional, so calculations of marginal and mixture distributions are an important tool. From an age-classified point of view, stage structure is a form of unobserved heterogeneity. From a stage-classified point of view, age structure is unobserved heterogeneity. In an age × stage-classified model, variance in demographic outcomes can be partitioned into contributions from both sources. Because these models are formulated as matrices, they are amenable to a complete sensitivity analysis. As more detailed and longer longitudinal studies are developed, age × stage-classified demography will become more common and more important.

Dataset Information

IntDb: A comprehensive database for classified introns of saccharomyces & human.

Publications

IntDb: A comprehensive database for classified introns of saccharomyces & human.

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