Predicting gene expression using morphological cell responses to nanotopography

Autor: Marie F. A. Cutiongco, Bjørn Sand Jensen, Paul M. Reynolds, Nikolaj Gadegaard

Publikováno v: Nature Communications, Vol 11, Iss 1, Pp 1-13 (2020)

The surface nanotopography of biomaterials direct cell behavior, but screening for desired effects is inefficient. Here, the authors introduce a platform that enables prediction of nanotopography-induced gene expression changes from changes in cell m

Externí odkaz: https://doaj.org/article/abc5b9a306914cf08639ce57a7f14882

Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis: Application to planar soft tissues

Autor: Ankush Aggarwal, Bjørn Sand Jensen, Sanjay Pant, Chung-Hao Lee

Publikováno v: Aggarwal, A, Jensen, B S, Pant, S & Lee, C-H 2023, ' Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis : Application to planar soft tissues ', Computer Methods in Applied Mechanics and Engineering, vol. 404, 115812 . https://doi.org/10.1016/j.cma.2022.115812

Data-based approaches are promising alternatives to the traditional analytical constitutive models for solid mechanics. Herein, we propose a Gaussian process (GP) based constitutive modeling framework, specifically focusing on planar, hyperelastic an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a1cbd6ddc9fc4c4be303cf80582c6e1
https://cronfa.swan.ac.uk/Record/cronfa62031/Download/62031__26074__bddb17d10bb84c8dbc0531d5d52c53bc.pdf

Predicting phenotype using morphological cell responses to nanotopography

Autor: Paul M. Reynolds, Marie F.A. Cutiongco, Nikolaj Gadegaard, Bjørn Sand Jensen

Cells respond in complex ways to topographies, making it challenging to identify a direct relationship between surface topography and cell response. A key problem is the lack of informative representations of topographical parameters that translate d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9a4a37b64d6c13d23490bf47d222f63

Learning Combinations of Multiple Feature Representations for Music Emotion Prediction

Autor: Bjørn Sand Jensen, Jan Larsen, Jens Madsen

Publikováno v: ASM@ACM Multimedia
Technical University of Denmark Orbit

Music consists of several structures and patterns evolving through time which greatly influences the human decoding of higher-level cognitive aspects of music like the emotions expressed in music. For tasks, such as genre, tag and emotion recognition

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25e44147fbbe62214747b67ba22159c7
https://doi.org/10.1145/2813524.2813534

Towards a universal representation for audio information retrieval and analysis

Autor: Rasmus Troelsgaard, Jan Larsen, Lars Kai Hansen, Bjørn Sand Jensen

Publikováno v: ICASSP

A fundamental and general representation of audio and music which integrates multi-modal data sources is important for both application and basic research purposes. In this paper we address this challenge by proposing a multi-modal version of the Lat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2553bfe00156b051e7fa4d8d4c84145a
https://doi.org/10.1109/icassp.2013.6638242