Biology subjects

Crook, S.

Publications and source records attributed to Crook, S..

4 recordsLinked to original sources

bioRxiv2018

Harmonizing semantic annotations for computational models in biology

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition, and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current semantic annotation practices among the COmputational Modeling in BIology NEtwork (COMBINE) community and provide a set of recommendations for building a consensus approach to semantic annotation.

scientific communication and education↗

bioRxiv2018

Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits

Computational models are powerful tools for investigating brain function in health and disease. However, biologically detailed neuronal and circuit models are complex and implemented in a range of specialized languages, making them inaccessible and opaque to many neuroscientists. This has limited critical evaluation of models by the scientific community and impeded their refinement and widespread adoption. To address this, we have combined advances in standardizing models, open source software development and web technologies to develop Open Source Brain, a platform for visualizing, simulating, disseminating and collaboratively developing standardized models of neurons and circuits from a range of brain regions. Model structure and parameters can be visualized and their dynamical properties explored through browser-controlled simulations, without writing code. Open Source Brain makes neural models transparent and accessible and facilitates testing, critical evaluation and refinement, thereby helping to improve the accuracy and reproducibility of models, and their dissemination to the wider community.

neuroscience↗

bioRxiv2017

SwarmSight: Real-Time Tracking of Insect Antenna Movements and Proboscis Extension Reflex using a Common Preparation and Conventional Hardware

Many scientifically and agriculturally important insects use antennae to detect the presence of volatile chemical compounds and extend their proboscis during feeding. The ability to rapidly obtain high-resolution measurements of natural antenna and proboscis movements and assess how they change in response to chemical, developmental, and genetic manipulations can aid the understanding of insect behavior. By extending our previous work on assessing aggregate insect swarm or animal group movements from natural and laboratory videos using video analysis software SwarmSight, we developed a novel, free, and open-source software module, SwarmSight Appendage Tracking (SwarmSight.org) for frame-by-frame tracking of insect antenna and proboscis positions from conventional web camera videos using conventional computers. The software processes frames about 120 times faster than humans, performs at better than human accuracy, and, using 30 frames-per-second videos, can capture antennal dynamics up to 15 Hz. We used the software to track the antennal response of honey bees to two odors and found significant mean antennal retractions away from the odor source about 1 s after odor presentation. We observed antenna position density heat map cluster formation and cluster and mean angle dependence on odor concentration.

animal behavior and cognition↗

bioRxiv2017

SNaReSim: Synthetic Nanopore Read Simulator

Nanopores represent the first commercial technology in decades to present a significantly different technique for DNA sequencing, and one of the first technologies to propose direct RNA sequencing. Despite significant differences with previous sequencing technologies, read simulators to date make similar assumptions with respect to error profiles and their analysis. This is a great disservice to both nanopore sequencing and to computer scientists who seek to optimize their tools for the platform. Previous works have discussed the occurrence of some k-mer bias, but this discussion has been focused on homopolymers, leaving unanswered the question of whether k-mer bias exists over general k-mers, how it occurs, and what can be done to reduce the effects. In this work, we demonstrate that current read simulators fail to accurately represent k-mer error distributions, We explore the sources of k-mer bias in nanopore basecalls, and we present a model for predicting k-mers that are difficult to identify. We also propose a new SNaReSim, a new state-of-the-art simulator, and demonstrate that it provides higher accuracy with respect to 6-mer accuracy biases.

bioinformatics↗