The microbiome and metatranscriptome of a panel from the mapping population reveal complex assembly and function involving host influence.

provide an optimal system for deciphering the host-microbiome interactions at various levels. We analyzed the pitcher microbiomes and metatranscriptomes of the parental species, and F1 and F2 generations from the mapping population ( X ) utilizing high-throughput sequencing methods. This study aimed to examine the host influences on the microbiome structure and function and to identify the key microbiome traits.

Chemical Entity Recognition for MEDLINE Indexing.

Chemical entity recognition is essential for indexing scientific literature in the MEDLINE database at the National Library of Medicine. However, the tool currently used to suggest terms for indexing, the Medical Text Indexer, was not originally conceived as a chemical recognition tool. It has instead been adapted to the task via its use of MetaMap and the addition of in-house patterns and rules.

Finding medication doses in the liteature.

Medication doses, one of the determining factors in medication safety and effectiveness, are present in the literature, but only in free-text form. We set out to determine if the systems developed for extracting drug prescription information from clinical text would yield comparable results on scientific literature and if sequence-to-sequence learning with neural networks could improve over the current state-of-the-art. We developed a collection of 694 PubMed Central documents annotated with drug dose information using the i2b2 schema.

A carnivorous plant genetic map: pitcher/insect-capture QTL on a genetic linkage map of .

The study of carnivorous plants can afford insight into their unique evolutionary adaptations and their interactions with prokaryotic and eukaryotic species. For (pitcher plants), we identified 64 quantitative trait loci (QTL) for insect-capture traits of the pitchers, providing the genetic basis for differences between the pitfall and lobster-trap strategies of insect capture. The linkage map developed here is based upon the F2 of a cross between and ; we mapped 437 single nucleotide polymorphism and simple sequence repeat markers.

A dataset of 200 structured product labels annotated for adverse drug reactions.

Adverse drug reactions (ADRs), unintended and sometimes dangerous effects that a drug may have, are one of the leading causes of morbidity and mortality during medical care. To date, there is no structured machine-readable authoritative source of known ADRs. The United States Food and Drug Administration (FDA) partnered with the National Library of Medicine to create a pilot dataset containing standardised information about known adverse reactions for 200 FDA-approved drugs.

MetaMap Lite: an evaluation of a new Java implementation of MetaMap.

MetaMap is a widely used named entity recognition tool that identifies concepts from the Unified Medical Language System Metathesaurus in text. This study presents MetaMap Lite, an implementation of some of the basic MetaMap functions in Java. On several collections of biomedical literature and clinical text, MetaMap Lite demonstrated real-time speed and precision, recall, and F1 scores comparable to or exceeding those of MetaMap and other popular biomedical text processing tools, clinical Text Analysis and Knowledge Extraction System (cTAKES) and DNorm.

Development of Transcriptomic Markers for Population Analysis Using Restriction Site Associated RNA Sequencing (RARseq).

We describe restriction site associated RNA sequencing (RARseq), an RNAseq-based genotype by sequencing (GBS) method. It includes the construction of RNAseq libraries from double stranded cDNA digested with selected restriction enzymes. To test this, we constructed six single- and six-dual-digested RARseq libraries from six F2 pitcher plant individuals and sequenced them on a half of a Miseq run.

Species tree estimation of diploid Helianthus (Asteraceae) using target enrichment.

Premise Of The Study: The sunflower genus Helianthus has long been recognized as economically significant, containing species of agricultural and horticultural importance. Additionally, this genus displays a large range of phenotypic and genetic variation, making Helianthus a useful system for studying evolutionary and ecological processes. Here we present the most robust Helianthus phylogeny to date, laying the foundation for future studies of this genus.

Resolving phylogenetic relationships of the recently radiated carnivorous plant genus Sarracenia using target enrichment.

The North American carnivorous pitcher plant genus Sarracenia (Sarraceniaceae) is a relatively young clade (<3 million years ago) displaying a wide range of morphological diversity in complex trapping structures. This recently radiated group is a promising system to examine the structural evolution and diversification of carnivorous plants; however, little is known regarding evolutionary relationships within the genus. Previous attempts at resolving the phylogeny have been unsuccessful, most likely due to few parsimony-informative sites compounded by incomplete lineage sorting.

Transcriptome analysis of sarracenia, an insectivorous plant.

Sarracenia species (pitcher plants) are carnivorous plants which obtain a portion of their nutrients from insects captured in the pitchers. To investigate these plants, we sequenced the transcriptome of two species, Sarracenia psittacina and Sarracenia purpurea, using Roche 454 pyrosequencing technology. We obtained 46 275 and 36 681 contigs by de novo assembly methods for S.

Development and characterization of microsatellite markers in Sarracenia L. (pitcher plant) species.

Sarracenia species (pitcher plants) are carnivorous plants which obtain a portion of their nutrients from insects captured in the pitchers. Sarracenia species naturally hybridize with each other, and hybrid swarms have been identified. A number of the taxa within the genus are considered endangered.

Journal descriptor indexing tool for categorizing text according to discipline or semantic type.

A JDI (Journal Descriptor Indexing) tool has been developed at NLM that automatically categorizes biomedical text as input, returning a ranked list, with scores between 0-1, of either JDs (Journal Descriptors, corresponding to biomedical disciplines) or STs (UMLS Semantic Types). Possible applications include WSD (Word Sense Disambiguation) and retrieval according to discipline. The Lexical Systems Group plans to distribute an open source JAVA version of this tool.

Word Sense Disambiguation by Selecting the Best Semantic Type Based on Journal Descriptor Indexing: Preliminary Experiment.

An experiment was performed at the National Library of Medicine((R)) (NLM((R))) in word sense disambiguation (WSD) using the Journal Descriptor Indexing (JDI) methodology. The motivation is the need to solve the ambiguity problem confronting NLM's MetaMap system, which maps free text to terms corresponding to concepts in NLM's Unified Medical Language System((R)) (UMLS((R))) Metathesaurus((R)). If the text maps to more than one Metathesaurus concept at the same high confidence score, MetaMap has no way of knowing which concept is the correct mapping.

The NLM Indexing Initiative's Medical Text Indexer.

The Medical Text Indexer (MTI) is a program for producing MeSH indexing recommendations. It is the major product of NLM's Indexing Initiative and has been used in both semi-automated and fully automated indexing environments at the Library since mid 2002. We report here on an experiment conducted with MEDLINE indexers to evaluate MTI's performance and to generate ideas for its improvement as a tool for user-assisted indexing.