Investigation of model stacking for drug sensitivity prediction

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2105

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Investigation of model stacking for drug sensitivity prediction ; volume:19 ; number:3 ; day:21 ; month:3 ; year:2018 ; pages:21-33 ; date:3.2018
BMC bioinformatics ; 19, Heft 3 (21.3.2018), 21-33, 3.2018

Classification: Biowissenschaften, Biologie

Creator: Matlock, Kevin

Contributor: De Niz, Carlos
Rahman, Raziur
Ghosh, Souparno
Pal, Ranadip
SpringerLink (Online service)

DOI: 10.1186/s12859-018-2060-2

URN: urn:nbn:de:1111-201805219452

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:51 AM CEST

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Matlock, Kevin
De Niz, Carlos
Rahman, Raziur
Ghosh, Souparno
Pal, Ranadip
SpringerLink (Online service)

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Efficient differentially private learning improves drug sensitivity prediction

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Sequential stacking link prediction algorithms for temporal networks

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Simultaneous prediction of RNA secondary structure and helix coaxial stacking

Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data

StackDPP: a stacking ensemble based DNA-binding protein prediction model

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Investigation of model stacking for drug sensitivity prediction

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Other Objects (12)

Network-based drug sensitivity prediction

A link prediction approach to cancer drug sensitivity prediction

Cancer drug sensitivity prediction from routine histology images

Efficient differentially private learning improves drug sensitivity prediction

Haze prediction method based on stacking learning

Application of transfer learning for cancer drug sensitivity prediction

Structural similarity assessment for drug sensitivity prediction in cancer

Sequential stacking link prediction algorithms for temporal networks

Stacking of antithrombotic drugs in cardiology: evidence-based customisation

Simultaneous prediction of RNA secondary structure and helix coaxial stacking

Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data

StackDPP: a stacking ensemble based DNA-binding protein prediction model

Network-based drug sensitivity prediction

A link prediction approach to cancer drug sensitivity prediction

Cancer drug sensitivity prediction from routine histology images

Efficient differentially private learning improves drug sensitivity prediction

Haze prediction method based on stacking learning

Application of transfer learning for cancer drug sensitivity prediction

Structural similarity assessment for drug sensitivity prediction in cancer

Sequential stacking link prediction algorithms for temporal networks

Stacking of antithrombotic drugs in cardiology: evidence-based customisation

Simultaneous prediction of RNA secondary structure and helix coaxial stacking

Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data

StackDPP: a stacking ensemble based DNA-binding protein prediction model

Network-based drug sensitivity prediction

A link prediction approach to cancer drug sensitivity prediction

Cancer drug sensitivity prediction from routine histology images

Efficient differentially private learning improves drug sensitivity prediction

Haze prediction method based on stacking learning

Application of transfer learning for cancer drug sensitivity prediction

Structural similarity assessment for drug sensitivity prediction in cancer

Sequential stacking link prediction algorithms for temporal networks

Stacking of antithrombotic drugs in cardiology: evidence-based customisation

Simultaneous prediction of RNA secondary structure and helix coaxial stacking

Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data

StackDPP: a stacking ensemble based DNA-binding protein prediction model

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