Eimear E Kenny

Dr. Eimear E Kenny


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2017 in The American Journal of Human Genetics
Verified
Journal Article
Closed access
AMALICIA MARTIN
ALICIA MARTIN
CGChristopher R. Gignoux
Christopher R. Gignoux
RWRaymond K. Walters
Raymond K. Walters
GWGenevieve L. Wojcik
Genevieve L. Wojcik
BNBenjamin M. Neale
Benjamin M. Neale
EKEimear E Kenny
Eimear E Kenny

1 August 2013 in The American Journal of Human Genetics
Verified
Journal Article
Closed access
BMBrian K. Maples
Brian K. Maples
SGSimon Gravel
Simon Gravel
EKEimear E Kenny
Eimear E Kenny
CBCarlos D. Bustamante
Carlos D. Bustamante

19 June 2019 in Nature
Verified
Journal Article
Closed access
PDF file
GWGenevieve L. Wojcik
Genevieve L. Wojcik
MGMariaelisa Graff
Mariaelisa Graff
KNKatherine K. Nishimura
Katherine K. Nishimura
RTRan Tao
Ran Tao
JHJeffrey Haessler
Jeffrey Haessler
CCChristopher S. Carlson
Christopher S. Carlson

21 September 2004 in PLOS Biology
Verified
Journal Article
Open access
PDF file
HMHans-Michael Müller
Hans-Michael Müller
EKEimear E Kenny
Eimear E Kenny
PSPaul W Sternberg
Paul W Sternberg
We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org.

1 March 2019 in Cell
Verified
Journal Article
Closed access
Noura Abul-HusnNoura Abul-Husn
Noura Abul-Husn
EKEimear E Kenny
Eimear E Kenny

26 December 2013 in PLOS Genetics
Verified
Journal Article
Open access
PDF file
SGSimon Gravel
Simon Gravel
FZFouad Zakharia
Fouad Zakharia
AMAndres Moreno-Estrada
Andres Moreno-Estrada
JBJake K. Byrnes
Jake K. Byrnes
MMMarina Muzzio
Marina Muzzio
CBCarlos D. Bustamante
Carlos D. Bustamante
There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is in MXL, in CLM, and in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern America ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas thousand years ago (kya), supports that the MXL Ancestors split kya, with a subsequent split of the ancestors to CLM and PUR kya. The model also features effective populations of in Mexico, in Colombia, and in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations. Populations of the Americas have a rich and heterogeneous genetic and cultural heritage that draws from a diversity of pre-Columbian Native American, European, and African populations. Characterizing this diversity facilitates the development of medical genetics research in diverse populations and the transfer of medical knowledge across populations. It also represents an opportunity to better understand the peopling of the Americas, from the crossing of Beringia to the post-Columbian era. Here, we take advantage sequencing of individuals of Colombian (CLM), Mexican (MXL), and Puerto Rican (PUR) origin by the 1000 Genomes project to improve our demographic models for the peopling of the Americas. The divergence among African, European, and Native American ancestors to these populations enables us to infer the continent of origin at each locus in the sampled genomes. The resulting patterns of ancestry suggest complex post-Columbian migration histories, starting later in CLM than in MXL and PUR. Whereas European ancestral segments show evidence of relatedness, a demographic model of synonymous variation suggests that the Native American Ancestors to MXL, PUR, and CLM panels split within a few hundred years over 12 thousand years ago. Together with early archeological sites in South America, these results support rapid divergence during the initial peopling of the Americas.