Hochschulschrift
Prediction of Protein Subcellular Location using Residue Exposure
- Weitere Titel
-
Vorhersage der subzellulären Lokalisation von Proteinen mittels der Zugänglichkeit von Aminosäuren
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Berlin, Freie Universität Berlin, Diss., 2014
- Schlagwort
-
Signaltransduktion
- Ereignis
-
Veröffentlichung
- (wo)
-
Berlin
- (wer)
-
Freie Universität Berlin
- (wann)
-
2014
- Urheber
-
Mer, Arvind Singh
- URN
-
urn:nbn:de:kobv:188-fudissthesis000000096489-8
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:54 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Hochschulschrift
Beteiligte
- Mer, Arvind Singh
- Freie Universität Berlin
Entstanden
- 2014
Ähnliche Objekte (12)
Prediction of protein subcellular location using residue exposure
Bayesian statistical approach for protein residue-residue contact Prediction
MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation
Model-based classification for subcellular localization prediction of proteins
Context Specific Next Location Prediction
Context specific next location prediction
Waste residue composites
Subcellular proteomics
Prediction of residue contacts and interaction sites in transmembrane proteins using deep learning
Context-specific subcellular localization prediction: Leveraging protein interaction networks and scientific texts
The residue of uniqueness
Acoustic emission based prediction of local stress exposure
Prediction of protein subcellular location using residue exposure
Bayesian statistical approach for protein residue-residue contact Prediction
MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation
Model-based classification for subcellular localization prediction of proteins
Context Specific Next Location Prediction
Context specific next location prediction
Waste residue composites
Subcellular proteomics
Prediction of residue contacts and interaction sites in transmembrane proteins using deep learning
Context-specific subcellular localization prediction: Leveraging protein interaction networks and scientific texts
The residue of uniqueness
Acoustic emission based prediction of local stress exposure
Prediction of protein subcellular location using residue exposure
Bayesian statistical approach for protein residue-residue contact Prediction
MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation
Model-based classification for subcellular localization prediction of proteins
Context Specific Next Location Prediction
Context specific next location prediction
Waste residue composites
Subcellular proteomics
Prediction of residue contacts and interaction sites in transmembrane proteins using deep learning
Context-specific subcellular localization prediction: Leveraging protein interaction networks and scientific texts
The residue of uniqueness