Publications by authors named "Philip MacMenamin"

Viruses in the genus Henipavirus encompass 2 highly pathogenic emerging zoonotic pathogens, Hendra virus (HeV) and Nipah virus (NiV). Despite the impact on human health, there is currently limited full-genome sequence information available for henipaviruses. This lack of full-length genomes hampers our ability to understand the molecular drivers of henipavirus emergence.

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Article Synopsis
  • There’s a growing interest in microbiome research, but many researchers struggle with the large datasets and complicated tools necessary for analysis.
  • The NIAID developed Nephele, a user-friendly, cloud-based platform that simplifies microbiome data analysis with set pipelines, making it easier for researchers to glean insights from their data.
  • Nephele uses Amazon Web Services for storage and processing, removing logistical burdens from researchers and making it more accessible.
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The cell-biological events that guide early-embryonic development occur with great precision within species but can be quite diverse across species. How these cellular processes evolve and which molecular components underlie evolutionary changes is poorly understood. To begin to address these questions, we systematically investigated early embryogenesis, from the one- to the four-cell embryo, in 34 nematode species related to C.

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Three-prime untranslated regions (3'UTRs) are widely recognized as important post-transcriptional regulatory regions of mRNAs. RNA-binding proteins and small non-coding RNAs such as microRNAs (miRNAs) bind to functional elements within 3'UTRs to influence mRNA stability, translation and localization. These interactions play many important roles in development, metabolism and disease.

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Background: Metazoan miRNAs regulate protein-coding genes by binding the 3' UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function.

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MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs.

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RNA interference (RNAi) is being used in large-scale genomic studies as a rapid way to obtain in vivo functional information associated with specific genes. How best to archive and mine the complex data derived from these studies provides a series of challenges associated with both the methods used to elicit the RNAi response and the functional data gathered. RNAiDB (RNAi Database; http://www.

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