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Protein Interaction Maps

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Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Biomolecular controlled annotations have become pivotal in computational biology, because they allow scientists to analyze large amounts of biological data to better understand test results, and to infer new knowledge. Yet, biomolecular annotation da...

Assessment of Semantic Similarity between Proteins Using Information Content and Topological Properties of the Gene Ontology Graph.

IEEE/ACM transactions on computational biology and bioinformatics
The semantic similarity between two interacting proteins can be estimated by combining the similarity scores of the GO terms associated with the proteins. Greater number of similar GO annotations between two proteins indicates greater interaction aff...

Improved prediction of protein-protein interactions using novel negative samples, features, and an ensemble classifier.

Artificial intelligence in medicine
Computational methods are employed in bioinformatics to predict protein-protein interactions (PPIs). PPIs and protein-protein non-interactions (PPNIs) display different levels of development, and the number of PPIs is considerably greater than that o...

A novel hierarchical selective ensemble classifier with bioinformatics application.

Artificial intelligence in medicine
Selective ensemble learning is a technique that selects a subset of diverse and accurate basic models in order to generate stronger generalization ability. In this paper, we proposed a novel learning algorithm that is based on parallel optimization a...

Predicting Protein-Protein Interaction Sites Using Sequence Descriptors and Site Propensity of Neighboring Amino Acids.

International journal of molecular sciences
Information about the interface sites of Protein-Protein Interactions (PPIs) is useful for many biological research works. However, despite the advancement of experimental techniques, the identification of PPI sites still remains as a challenging tas...

Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis.

Computational biology and chemistry
In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the avail...

Protein function in precision medicine: deep understanding with machine learning.

FEBS letters
Precision medicine and personalized health efforts propose leveraging complex molecular, medical and family history, along with other types of personal data toward better life. We argue that this ambitious objective will require advanced and speciali...

Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

Genetics and molecular research : GMR
Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks...

CLASH: Complementary Linkage with Anchoring and Scoring for Heterogeneous biomolecular and clinical data.

BMC medical informatics and decision making
BACKGROUND: The study on disease-disease association has been increasingly viewed and analyzed as a network, in which the connections between diseases are configured using the source information on interactome maps of biomolecules such as genes, prot...

Machine Learning of Protein Interactions in Fungal Secretory Pathways.

PloS one
In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict prote...