94 citations · 117 across the 11 of their papers we have counts for
11 papers
Causal identification with
Charles Tapley Hoyt, Craig Bakker, Richard J. Callahan +11
We present the Python package, which implements causal identification algorithms that apply interventional, counterfactual, and transportability queries to data from (randomi…
The Cell Ontology in the age of single-cell omics
Shawn Zheng Kai Tan, Aleix Puig-Barbe, Damien Goutte-Gattat +32
Single-cell omics technologies have transformed our understanding of cellular diversity by enabling high-resolution profiling of individual cells. However, the unprecedented scale…
Democratising Knowledge Representation with BioCypher
Sebastian Lobentanzer, Patrick Aloy, Jan Baumbach +26
Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate h…
A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs
Charles Tapley Hoyt, Max Berrendorf, Mikhail Galkin +2
The link prediction task on knowledge graphs without explicit negative triples in the training data motivates the usage of rank-based metrics. Here, we review existing rank-based m…
ChemicalX: A Deep Learning Library for Drug Pair Scoring
Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva +9
In this paper, we introduce ChemicalX, a PyTorch-based deep learning library designed for providing a range of state of the art models to solve the drug pair scoring task. The prim…
A Simple Standard for Sharing Ontological Mappings (SSSOM)
Nicolas Matentzoglu, James P. Balhoff, Susan M. Bello +41
Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representatio…
Statistical Model Checking based Analysis of Biological Networks
Bing Liu, Benjamin M. Gyori, P. S. Thiagarajan
We introduce a framework for analyzing ordinary differential equation (ODE) models of biological networks using statistical model checking (SMC). A key aspect of our work is the mo…
Approximate probabilistic verification of hybrid systems
Benjamin M. Gyori, Bing Liu, Soumya Paul +2
Hybrid systems whose mode dynamics are governed by non-linear ordinary differential equations (ODEs) are often a natural model for biological processes. However such models are dif…
Probabilistic verification of partially observable dynamical systems
Benjamin M. Gyori, Daniel Paulin, Sucheendra K. Palaniappan
The construction and formal verification of dynamical models is important in engineering, biology and other disciplines. We focus on non-linear models containing a set of parameter…
Hypothesis testing for Markov chain Monte Carlo
Benjamin M. Gyori, Daniel Paulin
Testing between hypotheses, when independent sampling is possible, is a well developed subject. In this paper, we propose hypothesis tests that are applicable when the samples are…
Non-asymptotic confidence intervals for MCMC in practice
Benjamin M. Gyori, Daniel Paulin
Using concentration inequalities, we give non-asymptotic confidence intervals for estimates obtained by Markov chain Monte Carlo (MCMC) simulations, when using the approximation $\…