An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot features

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1756-0381

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot features ; volume:14 ; number:1 ; day:20 ; month:1 ; year:2021 ; pages:1-17 ; date:12.2021
BioData Mining ; 14, Heft 1 (20.1.2021), 1-17, 12.2021

Creator: An, Ji-Yong
Meng, Fan-Rong
Yan, Zi-Ji

Contributor: SpringerLink (Online service)

DOI: 10.1186/s13040-021-00242-1

URN: urn:nbn:de:101:1-2021031120305337874043

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:37 AM CEST

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An, Ji-Yong
Meng, Fan-Rong
Yan, Zi-Ji
SpringerLink (Online service)

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Do Speed and Proximity Affect Human-Robot Collaboration with an Industrial Robot Arm?

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An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot features

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Other Objects (12)

Sequence-based drug-target affinity prediction using weighted graph neural networks

Modelling extreme wind speeds

SSELM-neg: spherical search-based extreme learning machine for drug–target interaction prediction

Do Speed and Proximity Affect Human-Robot Collaboration with an Industrial Robot Arm?

Detection and characterization of extreme wind speed ramps

Exploring drug-target interaction networks of illicit drugs

Drug–target interaction prediction via multiple classification strategies

Robot Speed Adaption in Multiple Trajectory Planning and Integration in a Simulation Tool for Human-Robot Interaction

Task allocation model for human-robot collaboration with variable cobot speed

DASPfind: new efficient method to predict drug–target interactions

Explainable deep drug–target representations for binding affinity prediction

Prediction of drug–target interactions through multi-task learning

Sequence-based drug-target affinity prediction using weighted graph neural networks

Modelling extreme wind speeds

SSELM-neg: spherical search-based extreme learning machine for drug–target interaction prediction

Do Speed and Proximity Affect Human-Robot Collaboration with an Industrial Robot Arm?

Detection and characterization of extreme wind speed ramps

Exploring drug-target interaction networks of illicit drugs

Drug–target interaction prediction via multiple classification strategies

Robot Speed Adaption in Multiple Trajectory Planning and Integration in a Simulation Tool for Human-Robot Interaction

Task allocation model for human-robot collaboration with variable cobot speed

DASPfind: new efficient method to predict drug–target interactions

Explainable deep drug–target representations for binding affinity prediction

Prediction of drug–target interactions through multi-task learning

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Do Speed and Proximity Affect Human-Robot Collaboration with an Industrial Robot Arm?

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Drug–target interaction prediction via multiple classification strategies

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Task allocation model for human-robot collaboration with variable cobot speed

DASPfind: new efficient method to predict drug–target interactions

Explainable deep drug–target representations for binding affinity prediction

Prediction of drug–target interactions through multi-task learning

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