Biology subjects

Hoffman, A. S.

Publications and source records attributed to Hoffman, A. S..

3 recordsLinked to original sources

bioRxiv2021

RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine

BackgroundBiomedical translational science is increasingly using computational reasoning on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome, DrugBank, and SMPDB in order to facilitate discovery of new therapeutic targets and modalities. The NCATS Biomedical Data Translator project is working to federate autonomous reasoning agents and knowledge providers within a distributed system for answering translational questions. Within that project and the broader field, there is a need for a framework that can efficiently and reproducibly build an integrated, standards-compliant, and comprehensive biomedical knowledge graph that can be downloaded in standard serialized form or queried via a public application programming interface (API). ResultsTo create a knowledge provider system within the Translator project, we have developed RTX-KG2, an open-source software system for building--and hosting a web API for querying--a biomedical knowledge graph that uses an Extract-Transform-Load (ETL) approach to integrate 70 knowledge sources (including the aforementioned core six sources) into a knowledge graph with provenance information including (where available) citations. The semantic layer and schema for RTX-KG2 follow the standard Biolink model to maximize interoperability. RTX-KG2 is currently being used by multiple Translator reasoning agents, both in its downloadable form and via its SmartAPI-registered interface. Serializations of RTX-KG2 are available for download in both the pre-canonicalized form and in canonicalized form (in which synonyms are merged). The current canonicalized version (KG2.7.3) of RTX-KG2 contains 6.4M nodes and 39.3M edges with a hierarchy of 77 relationship types from Biolink. ConclusionRTX-KG2 is the first knowledge graph that integrates UMLS, SemMedDB, ChEMBL, DrugBank, Reactome, SMPDB, and 64 additional knowledge sources within a knowledge graph that conforms to the Biolink standard for its semantic layer and schema. RTX-KG2 is publicly available for querying via its API at arax.rtx.ai/api/rtxkg2/v1.2/openapi.json. The code to build RTX-KG2 is publicly available at github:RTXteam/RTX-KG2.

bioinformatics↗

bioRxiv2020

Variation in behavior drives multiscale responses to habitat conditions in timber rattlesnakes (Crotalus horridus)

Variations in both the behavior of wildlife and the scale at which the environment most influences the space use of wild animals (i.e., scale of effect) are critical, but often overlooked in habitat selection modeling. Ecologists have proposed that biological responses happening over longer time frames are influenced by environmental variables at larger spatial scales, but this has rarely been empirically tested. Here, we hypothesized that long-term patterns of behavior (i.e. lasting multiple weeks to months) would be associated with larger scales of effect than more sporadic behaviors. We predicted site use by 43 radio-telemetered timber rattlesnakes (Crotalus horridus) exhibiting four distinct, time-varying behaviors (foraging, digestion, ecdysis, and gestation) using remotely-sensed environmental variables related to forest structure and landscape topography. Among sites used by snakes, warmer temperatures and higher levels of forest disturbance were predictive of behaviors dependent on thermoregulation including gestation and ecdysis while more moderate temperatures and drier, more oak-dominated sites were predictive of foraging. Long-term behaviors were associated with larger spatial scales, supporting our hypothesis that the scale at which habitat selection occurs is linked to the temporal scale of relevant behaviors. Management recommendations based on single-scale models of habitat use that do not account for fine-scale variations in behavior may obscure the importance of potentially limiting habitat features needed for infrequent behaviors that are critically important for growth and reproduction of this and related species.

ecology↗

bioRxiv2020

Prey-Driven Behavioral Habitat Use in a Low-Energy Ambush Predator

O_LIFood acquisition is an important modulator of animal behavior and habitat selection that can affect fitness. Optimal foraging theory predicts that predators should select habitat patches to maximize their foraging success and net energy gain, which predators can achieve by targeting spaces with high prey availability. However, it is debated whether prey availability drives fine-scale habitat selection for predators. C_LIO_LIWe assessed whether an ambush predator, the timber rattlesnake (Crotalus horridus), exhibits optimal foraging site selection based on the spatial distribution and availability of prey. C_LIO_LIWe evaluated the spatial concordance of radio-telemetered timber rattlesnake foraging locations and passive infrared game camera trap detections of potential small mammal prey (Peromyscus spp., Tamias striatus, and Sciurus spp.) in a mixed-use forest in southeastern Ohio from 2016-2019. We replicated a characteristic timber rattlesnake ambush position by focusing cameras over logs and modeled small mammal encounters across the landscape in relation to remotely-sensed forest and landscape structural features. To determine whether snakes selectively forage in areas with higher prey availability, we projected the estimated prey spatial relationships across the landscape and modeled their overlap of occurrence with observed timber rattlesnake foraging locations. C_LIO_LIWe broadly predicted that prey availability was greatest in mature deciduous forests, but T. striatus and Sciurus spp. exhibited greater spatial heterogeneity compared to Peromyscus spp. We also combined predicted species encounter rates to encompass a body size gradient in potential prey. The spatial distribution of cumulative small mammal encounters (i.e. overall prey availability), rather than the distribution of any one species, was highly predictive of snake foraging. C_LIO_LITimber rattlesnakes appear to select foraging locations where the probability of encountering prey is greatest. Our study provides evidence for fine-scale optimal foraging in a low-energy, ambush predator and offers new insights into drivers of snake foraging and habitat selection. C_LI

ecology↗