Matches in SemOpenAlex for { <https://semopenalex.org/work/W2257760190> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W2257760190 abstract "Recent advances in experimental biology have made available vast amounts of quantitative data describing the complex systems under study; unfortunately there exists a bottleneck in extracting biologically-revelant information from these data. We present here methods for inferring such information from biological image and network data, in which probabilistic models are proposed and statistical inference is used to calculate the parameters and complexity of these models from observed data. We first present an automated scheme to segment cells in micrograph data and infer leading-edge velocities from time-lapse micrograph sequences. We then show applications of this scheme to several high-throughput studies of cell motility which provide key insight into biophysical models of cell locomotion; results include calculations of spatiotemporal correlations in lateral waves at the cell edge and a fundamental understanding of T cell migration. We then extend our work on image segmentation to the problem of segmenting biological networks, i.e. module discovery. We propose a probabilistic model for modular networks and present a principled, efficient, and interpretable algorithm for approximate Bayesian inference of the model parameters and complexity. We elucidate analogies between module discovery and disorder-averaged spin-glass calculations and show how several existing methods for finding modules can be described as special, variant, or limiting cases of our work. Finally, we apply the technique to synthetic and real networks and outline how the method naturally allows selection among competing network models." @default.
- W2257760190 created "2016-06-24" @default.
- W2257760190 creator A5058073294 @default.
- W2257760190 creator A5085649470 @default.
- W2257760190 date "2008-01-01" @default.
- W2257760190 modified "2023-09-23" @default.
- W2257760190 title "Statistical inference for biophysical image and network data" @default.
- W2257760190 hasPublicationYear "2008" @default.
- W2257760190 type Work @default.
- W2257760190 sameAs 2257760190 @default.
- W2257760190 citedByCount "0" @default.
- W2257760190 crossrefType "journal-article" @default.
- W2257760190 hasAuthorship W2257760190A5058073294 @default.
- W2257760190 hasAuthorship W2257760190A5085649470 @default.
- W2257760190 hasConcept C11413529 @default.
- W2257760190 hasConcept C114289077 @default.
- W2257760190 hasConcept C124101348 @default.
- W2257760190 hasConcept C149635348 @default.
- W2257760190 hasConcept C153180895 @default.
- W2257760190 hasConcept C154945302 @default.
- W2257760190 hasConcept C160920958 @default.
- W2257760190 hasConcept C162307627 @default.
- W2257760190 hasConcept C2776214188 @default.
- W2257760190 hasConcept C2780513914 @default.
- W2257760190 hasConcept C33724603 @default.
- W2257760190 hasConcept C41008148 @default.
- W2257760190 hasConcept C49937458 @default.
- W2257760190 hasConcept C89600930 @default.
- W2257760190 hasConceptScore W2257760190C11413529 @default.
- W2257760190 hasConceptScore W2257760190C114289077 @default.
- W2257760190 hasConceptScore W2257760190C124101348 @default.
- W2257760190 hasConceptScore W2257760190C149635348 @default.
- W2257760190 hasConceptScore W2257760190C153180895 @default.
- W2257760190 hasConceptScore W2257760190C154945302 @default.
- W2257760190 hasConceptScore W2257760190C160920958 @default.
- W2257760190 hasConceptScore W2257760190C162307627 @default.
- W2257760190 hasConceptScore W2257760190C2776214188 @default.
- W2257760190 hasConceptScore W2257760190C2780513914 @default.
- W2257760190 hasConceptScore W2257760190C33724603 @default.
- W2257760190 hasConceptScore W2257760190C41008148 @default.
- W2257760190 hasConceptScore W2257760190C49937458 @default.
- W2257760190 hasConceptScore W2257760190C89600930 @default.
- W2257760190 hasLocation W22577601901 @default.
- W2257760190 hasOpenAccess W2257760190 @default.
- W2257760190 hasPrimaryLocation W22577601901 @default.
- W2257760190 hasRelatedWork W1169768527 @default.
- W2257760190 hasRelatedWork W1529075176 @default.
- W2257760190 hasRelatedWork W1755705917 @default.
- W2257760190 hasRelatedWork W1863027961 @default.
- W2257760190 hasRelatedWork W2038716712 @default.
- W2257760190 hasRelatedWork W2100344688 @default.
- W2257760190 hasRelatedWork W2104915027 @default.
- W2257760190 hasRelatedWork W2126912391 @default.
- W2257760190 hasRelatedWork W2133182391 @default.
- W2257760190 hasRelatedWork W2154293840 @default.
- W2257760190 hasRelatedWork W2161511352 @default.
- W2257760190 hasRelatedWork W2284116776 @default.
- W2257760190 hasRelatedWork W2426525045 @default.
- W2257760190 hasRelatedWork W2613518882 @default.
- W2257760190 hasRelatedWork W2789065061 @default.
- W2257760190 hasRelatedWork W3130233321 @default.
- W2257760190 hasRelatedWork W3179328596 @default.
- W2257760190 hasRelatedWork W3212275538 @default.
- W2257760190 hasRelatedWork W621724587 @default.
- W2257760190 hasRelatedWork W639101660 @default.
- W2257760190 isParatext "false" @default.
- W2257760190 isRetracted "false" @default.
- W2257760190 magId "2257760190" @default.
- W2257760190 workType "article" @default.