arXiv subjects

Cheryl Telmer

Publications and source records attributed to Cheryl Telmer.

3 recordsLinked to original sources

arXiv2021

New advances in the automation of context-aware information selection and guided model assembly

The automated assembly and extension of dynamic network models using information extracted from literature are challenging due to the amount and inconsistency in published literature. Recently, efforts have been made to automatically and efficiently assemble the information extracted from literature into models. In this review, we summarize the basic concept, performance, advantages, and limitations of five automated extension methods. Each method was tested for its ability to reconstruct a model of T-cell differentiation as compared against a number of predefined system properties.

q-bio.MN↗

arXiv2020

ACCORDION: Clustering and Selecting Relevant Data for Guided Network Extension and Query Answering

Querying new information from knowledge sources, in general, and published literature, in particular, aims to provide precise and quick answers to questions raised about a system under study. In this paper, we present ACCORDION (Automated Clustering Conditional On Relating Data of Interactions tO a Network), a novel tool and a methodology to enable efficient answering of biological questions by automatically assembling new, or expanding existing models using published literature. Our approach integrates information extraction and clustering with simulation and formal analysis to allow for an automated iterative process that includes assembling, testing and selecting the most relevant models, given a set of desired system properties. We applied our methodology to a model of the circuitry that con-trols T cell differentiation. To evaluate our approach, we compare the model that we obtained, using our automated model extension approach, with the previously published manually extended T cell differentiation model. Besides demonstrating automated and rapid reconstruction of a model that was previously built manually, ACCORDION can assemble multiple models that satisfy desired properties. As such, it replaces large number of tedious or even imprac-tical manual experiments and guides alternative hypotheses and interventions in biological systems.

q-bio.MN↗

arXiv2017

Methods to Expand Cell Signaling Models using Automated Reading and Model Checking

Biomedical research results are being published at a high rate, and with existing search engines, the vast amount of published work is usually easily accessible. However, reproducing published results, either experimental data or observations is often not viable. In this work, we propose a framework to overcome some of the issues of reproducing previous research, and to ensure re-usability of published information. We present here a framework that utilizes the results from state-of-the-art biomedical literature mining, biological system modeling and analysis techniques, and provides means to scientists to assemble and reason about information from voluminous, fragmented and sometimes inconsistent literature. The overall process of automated reading, assembly and reasoning can speed up discoveries from the order of decades to the order of hours or days. Our framework described here allows for rapidly conducting thousands of in silico experiments that are designed as part of this process.

q-bio.MN↗