AIMC Topic: Computational Biology

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BagReg: Protein inference through machine learning.

Computational biology and chemistry
Protein inference from the identified peptides is of primary importance in the shotgun proteomics. The target of protein inference is to identify whether each candidate protein is truly present in the sample. To date, many computational methods have ...

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation.

BMC systems biology
BACKGROUND: DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Identification of DNA-binding proteins is one of the major challenges in the field of genome...

Aber-OWL: a framework for ontology-based data access in biology.

BMC bioinformatics
BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within t...

An integrated breast cancer risk assessment and management model based on fuzzy cognitive maps.

Computer methods and programs in biomedicine
BACKGROUND: There is a growing demand for women to be classified into different risk groups of developing breast cancer (BC). The focus of the reported work is on the development of an integrated risk prediction model using a two-level fuzzy cognitiv...

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

BMC genomics
BACKGROUND: Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large ...

ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors.

BMC bioinformatics
BACKGROUND: microRNAs (miRNAs) play a vital role in development, oncogenesis, and apoptosis by binding to mRNAs to regulate the posttranscriptional level of coding genes in mammals, plants, and insects. Recent studies have demonstrated that the expre...

Extracting Various Classes of Data From Biological Text Using the Concept of Existence Dependency.

IEEE journal of biomedical and health informatics
One of the key goals of biological natural language processing (NLP) is the automatic information extraction from biomedical publications. Most current constituency and dependency parsers overlook the semantic relationships between the constituents c...

Evolving a Behavioral Repertoire for a Walking Robot.

Evolutionary computation
Numerous algorithms have been proposed to allow legged robots to learn to walk. However, most of these algorithms are devised to learn walking in a straight line, which is not sufficient to accomplish any real-world mission. Here we introduce the Tra...

More challenges for machine-learning protein interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Machine learning may be the most popular computational tool in molecular biology. Providing sustained performance estimates is challenging. The standard cross-validation protocols usually fail in biology. Park and Marcotte found that even...