Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model

<p>Abstract</p> <p>Background</p> <p>Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is generally achieved by extracting concepts overrepresented in the gene lists. This analysis often depends on manual annotation of genes based on controlled vocabularies, in particular, Gene Ontology (GO). However, the annotation of genes is a labor-intensive process; and the vocabularies are generally incomplete, leaving some important biological domains inadequately covered.</p> <p>Results</p> <p>We propose a statistical method that uses the primary literature, i.e. free-text, as the source to perform overrepresentation analysis. The method is based on a statistical framework of mixture model and addresses the methodological flaws in several existing programs. We implemented this method within a literature mining system, BeeSpace, taking advantage of its analysis environment and added features that facilitate the interactive analysis of gene sets. Through experimentation with several datasets, we showed that our program can effectively summarize the important conceptual themes of large gene sets, even when traditional GO-based analysis does not yield informative results.</p> <p>Conclusions</p> <p>We conclude that the current work will provide biologists with a tool that effectively complements the existing ones for overrepresentation analysis from genomic experiments. Our program, Genelist Analyzer, is freely available at: <url>http://workerbee.igb.uiuc.edu:8080/BeeSpace/Search.jsp</url></p

Method of Increasing Mass Transfer Rate of Acid Gas Scrubbing Solvents

A method and catalysts for increasing the overall mass transfer rate of acid gas scrubbing solids is disclosed. Various catalyst compounds for that purpose are also disclosed

Enhancements in Mass Transfer for Carbon Capture Solvents Part I: Homogeneous Catalyst

The novel small molecule carbonic anhydrase (CA) mimic [CoIII(Salphen-COO−)Cl]HNEt3 (1), was synthesized as an additive for increasing CO2 absorption rates in amine-based post-combustion carbon capture processes (CCS), and its efficacy was verified. 1 was designed for use in a kinetically slow but thermally stable blended solvent, containing the primary amines 1-amino-2-propanol (A2P) and 2-amino-2-methyl-1-propanol (AMP). Together, the A2P/AMP solvent and 1 reduce the overall energy penalty associated with CO2 capture from coal-derived flue gas, relative to the baseline solvent MEA. 1 is also effective at increasing absorption kinetics of kinetically fast solvents, such as MEA, which can reduce capital costs by requiring a smaller absorber tower. The transition from catalyst testing under idealized laboratory conditions, to process relevant lab- and bench-scale testing adds many additional variables that are not well understood and rarely discussed. The stepwise testing of both 1 and the novel A2P/AMP solvent blend is described through a transition process that identifies many of these process and evaluation challenges not often addressed when designing a chemical or catalytic additive for industrial CCS systems, where consideration of solvent chemistry is typically the primary goal

BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature

With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php

Neurogenomic and neurochemical dissection of honey bee dance communication

Honey bee dance communication is a classic form of animal behavior, with over 70 years of intense study. In this chapter, we first discuss conceptually how it is possible to dissect dance communication into simpler behavioral modules for neurogenomics analysis, based on information from prior ethological studies of dance behavior and a rapidly advancing functional analysis of the insect brain. We then review recent studies that have used this conceptual approach and new genomic tools to begin to explore neurogenomic and neurochemical aspects of dance communication, highlighting the following findings. Comparative transcriptomic studies of specific brain regions across Apis species that differ in dance behavior have implicated genes involved in the geotactic and odometric elements of dance, and genes involved in learning and memory systems and the circadian clock as important modulators of dance output. This research also has identified distinct patterns of gene expression in different brain regions that provide additional hints about the regulation of dance behavior. Pharmacological studies with octopamine and related compounds have demonstrated the role of the reward system in modulating the likelihood that a bee will dance upon returning from a foraging trip. The results of these early studies provide a foundation for a more comprehensive molecular dissection of dance behavior and suggest that the mechanisms regulating dance communication involve evolutionary reuse and adaptation of neuromolecular systems that control elements of solitary behavior.17 page(s

Traditional healthcare practices among the Tagin tribe of Arunachal Pradesh

127-130The Tagin tribe is an indigenous group of people living at upper Subansiri district of Arunachal Pradesh. A study on practice of Traditional Medicine (TM) was carried out among these people. The result documented 10 medicinal plants used by the Traditional Medicinal Practitioner (TMS) of Tagin tribe for use in traditional medicine. Fresh leaves, fruits, bark and stems are reported be used in TM for treatment of ailments like diarrhoea, jaundice, wound healing, fever, etc

Mean forager by one-day-old brain gene expression ratio (F/DO) of two example fly ortholog genes that show interesting patterns of difference between especially and

<p><b>Copyright information:</b></p><p>Taken from "Species differences in brain gene expression profiles associated with adult behavioral maturation in honey bees"</p><p>http://www.biomedcentral.com/1471-2164/8/202</p><p>BMC Genomics 2007;8():202-202.</p><p>Published online 29 Jun 2007</p><p>PMCID:PMC1929079.</p><p></p> Species key: AF = , AC = , AM = , AD = . Different letters of the alphabet depict significantly different mean values according to a post-hoc Tukey's test on an ANOVA of the F/DO ratios

Transcriptomic profiling of central nervous system regions in three species of honey bee during dance communication behavior.

BACKGROUND:We conducted a large-scale transcriptomic profiling of selected regions of the central nervous system (CNS) across three species of honey bees, in foragers that were performing dance behavior to communicate to their nestmates the location, direction and profitability of an attractive floral resource. We used microarrays to measure gene expression in bees from Apis mellifera, dorsata and florea, species that share major traits unique to the genus and also show striking differences in biology and dance communication. The goals of this study were to determine the extent of regional specialization in gene expression and to explore the molecular basis of dance communication. PRINCIPAL FINDINGS:This "snapshot" of the honey bee CNS during dance behavior provides strong evidence for both species-consistent and species-specific differences in gene expression. Gene expression profiles in the mushroom bodies consistently showed the biggest differences relative to the other CNS regions. There were strong similarities in gene expression between the central brain and the second thoracic ganglion across all three species; many of the genes were related to metabolism and energy production. We also obtained gene expression differences between CNS regions that varied by species: A. mellifera differed the most, while dorsata and florea tended to be more similar. SIGNIFICANCE:Species differences in gene expression perhaps mirror known differences in nesting habit, ecology and dance behavior between mellifera, florea and dorsata. Species-specific differences in gene expression in selected CNS regions that relate to synaptic activity and motor control provide particularly attractive candidate genes to explain the differences in dance behavior exhibited by these three honey bee species. Similarities between central brain and thoracic ganglion provide a unique perspective on the potential coupling of these two motor-related regions during dance behavior and perhaps provide a snapshot of the energy intensive process of dance output generation. Mushroom body results reflect known roles for this region in the regulation of learning, memory and rhythmic behavior