Algorithms to Explore the Structure and Evolution of Biological Networks
Explore this paper's citation graph
Summary
This thesis proposes a collection of novel algorithms to explore the structure and evolution of large, noisy, and sparsely annotated biological networks, and introduces two information-theoretic algorithms to extract interesting patterns and modules embedded in large graphs.
- Type
- dissertation
- Published
- 2010-01-01
- Cited by
- 0
- References
- 313
- OpenAlex
- https://openalex.org/W25912597
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:37050207
Keywords
Automatic summarization, Computer science, Biological network, Theoretical computer science, Probabilistic logic
References
- A Propagation-based Algorithm for Inferring Gene-Disease Assocations
- Not All Scale-Free Networks Are Born Equal: The Role of the Seed Graph in PPI Network Evolution
- The Brede database: a small database for functional neuroimaging
- Collective entity resolution in relational data
- A Bootstrap Approach to Martian Manufacturing
- A network of protein–protein interactions in yeast
- Metagenomic and functional analysis of hindgut microbiota of a wood-feeding higher termite
- CYGD: the Comprehensive Yeast Genome Database
- MDL Summarization with Holes
- Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data
- Discovering Large Dense Subgraphs in Massive Graphs
- From molecular to modular cell biology
- The human brain is intrinsically organized into dynamic, anticorrelated functional networks.
- Evaluation of clustering algorithms for protein-protein interaction networks
- Histogram-Based Approximation of Set-Valued Query-Answers
- Selection of informative clusters from hierarchical cluster tree with gene classes
- Semantic Compression and Pattern Extraction with Fascicles
- Identification of functional modules using network topology and high-throughput data
- Network Archaeology: Uncovering Ancient Networks from Present-Day Interactions
- Extraction of phylogenetic network modules from the metabolic network
Cited by
No citing papers recorded for this paper.
Related papers
- HetNetAligner: Design and Implementation of an algorithm for heterogeneous network alignment on Apache Spark
- A novel method for large scale graph exploration
- Network Summarization with Preserved Spectral Properties
- Summarizing Network Processes with Network-Constrained Boolean Matrix Factorization
- Discrimination of unknown complex network based on the information of local nodes
- Learning patterns in dynamic graphs with application to biological networks
- Evolutionary Network Embedding Preserving Both Local Proximity and Community Structure
- HetNetAligner: A Novel Algorithm for Local Alignment of Heterogeneous Biological Networks