Monografie
New approaches and software for sequence function prediction and gene design integrating specific knowledge on protein structure and translation
- Sprache
-
Englisch
- Identifier
-
1254161678
Thema
Design
Beteiligte Personen und Organisationen
Simm, Dominic Alexander
Waack, Stephan
Waack, Stephan
Kollmar, Martin
Waack, Stephan
Waack, Stephan
Kollmar, Martin
- URN
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
26.01.2023, 13:58 MEZ
Objekttyp
- Monografie
Beteiligte
- Simm, Dominic Alexander
- Waack, Stephan
- Waack, Stephan
- Kollmar, Martin
Ähnliche Objekte (12)
Fast methods for metagenomic sequence search and annotation
A Bioinformatics Pipeline for Identifying Dysregulated Pathways in Cancer from Comparative RNA-Seq Transcriptome Analysis
German Conference on Bioinformatics 2013 (GCB 2013)
Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory
Machine learning and statistical analysis to identify determinants of survival in primary glioblastoma using genome wide expression studies
Prediction of Protein-Protein Interaction Sites with Conditional Random Fields
Barycenters and ANOVA for Point Pattern Data
Limit Laws for Empirical Optimal Transport
Development of Agent-Based Simulation Models for Software Evolution
Probabilistic models for protein conformational changes
Classifiers for Discrimination of Significant Protein Residues and Protein-Protein Interaction Using Concepts of Information Theory and Machine Learning
Developer-Centric Software Assessment
Fast methods for metagenomic sequence search and annotation
A Bioinformatics Pipeline for Identifying Dysregulated Pathways in Cancer from Comparative RNA-Seq Transcriptome Analysis
German Conference on Bioinformatics 2013 (GCB 2013)
Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory
Machine learning and statistical analysis to identify determinants of survival in primary glioblastoma using genome wide expression studies
Prediction of Protein-Protein Interaction Sites with Conditional Random Fields
Barycenters and ANOVA for Point Pattern Data
Limit Laws for Empirical Optimal Transport
Development of Agent-Based Simulation Models for Software Evolution
Probabilistic models for protein conformational changes
Classifiers for Discrimination of Significant Protein Residues and Protein-Protein Interaction Using Concepts of Information Theory and Machine Learning
Developer-Centric Software Assessment
Fast methods for metagenomic sequence search and annotation
A Bioinformatics Pipeline for Identifying Dysregulated Pathways in Cancer from Comparative RNA-Seq Transcriptome Analysis
German Conference on Bioinformatics 2013 (GCB 2013)
Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory
Machine learning and statistical analysis to identify determinants of survival in primary glioblastoma using genome wide expression studies
Prediction of Protein-Protein Interaction Sites with Conditional Random Fields
Barycenters and ANOVA for Point Pattern Data
Limit Laws for Empirical Optimal Transport
Development of Agent-Based Simulation Models for Software Evolution
Probabilistic models for protein conformational changes
Classifiers for Discrimination of Significant Protein Residues and Protein-Protein Interaction Using Concepts of Information Theory and Machine Learning