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Foote, B.

Publications and source records attributed to Foote, B..

2 recordsLinked to original sources

Spotty distributions: Spotted Gar (Lepisosteus oculatus) and Spotted Sucker (Minytrema melanops) range expansion in eastern Lake Erie

Natural range expansions in warm-water freshwater fishes are currently not well understood, but shifts in native species distributions can be influenced by many factors, including habitat restoration or degradation and climate change. Here, we provide empirical evidence of range expansions observed in two native freshwater fish species in Lake Erie: the Spotted Gar (Lepisosteus oculatus) and Spotted Sucker (Minytrema melanops). We confirmed our field identifications of L. oculatus and M. melanops using mtDNA barcoding. Maximum likelihood phylogenetic analyses reveal that our samples confidently resolve in the L. oculatus and M. melanops clades respectively, with additional identification support from BLAST searches. Notably, we found no correlation between the increased detection rate of both species and an increase in sampling effort when compared to previous records. Historically, eastern Lake Erie experienced habitat degradation through channelization, siltation, dredging, and toxification of sediments. We hypothesize that recent habitat remediation efforts have provided suitable habitat for both species to recolonize shallow waters with densely vegetated habitat (>90% substrate coverage). Both species are likely to continue their northern expansion as habitats are restored and climatic changes favor warm-water fishes.

zoology↗

Knowledge graph analytics platform with LINCS and IDG for Parkinson's disease target illumination

BackgroundLINCS, "Library of Integrated Network-based Cellular Signatures", and IDG, "Illuminating the Druggable Genome", are both NIH projects and consortia that have generated rich datasets for the study of the molecular basis of human health and disease. LINCS L1000 expression signatures provide unbiased systems/omics experimental evidence. IDG provides compiled and curated knowledge for illumination and prioritization of novel drug target hypotheses. Together, these resources can support a powerful new approach to identifying novel drug targets for complex diseases, such as Parkinsons disease (PD), which continues to inflict severe harm on human health, and resist traditional research approaches. ResultsIntegrating LINCS and IDG, we built the Knowledge Graph Analytics Platform (KGAP) to support an important use case: identification and prioritization of drug target hypotheses for associated diseases. The KGAP approach includes strong semantics interpretable by domain scientists and a robust, high performance implementation of a graph database and related analytical methods. Illustrating the value of our approach, we investigated results from queries relevant to PD. Approved PD drug indications from IDGs resource DrugCentral were used as starting points for evidence paths exploring chemogenomic space via LINCS expression signatures for associated genes, evaluated as target hypotheses by integration with IDG. The KG-analytic scoring function was validated against a gold standard dataset of genes associated with PD as elucidated, published mechanism-of-action drug targets, also from DrugCentral. IDGs resource TIN-X was used to rank and filter KGAP results for novel PD targets, and one, SYNGR3 (Synaptogyrin-3), was manually investigated further as a case study and plausible new drug target for PD. ConclusionsThe synergy of LINCS and IDG, via KG methods, empowers graph analytics methods for the investigation of the molecular basis of complex diseases, and specifically for identification and prioritization of novel drug targets. The KGAP approach enables downstream applications via integration with resources similarly aligned with modern KG methodology. The generality of the approach indicates that KGAP is applicable to many disease areas, in addition to PD, the focus of this paper.

bioinformatics↗