AIMC Topic: Computational Biology

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Patient-specific early classification of multivariate observations.

International journal of data mining and bioinformatics Jan 1, 2015
Early classification of time series has been receiving a lot of attention recently. In this paper we present a model, which we call the Early Classification Model (ECM), that allows for early, accurate and patient-specific classification of multivari...
Computational Biology Gene Expression Profiling Diagnosis, Computer-Assisted Support Vector Machine Markov Chains Sepsis Humans Multiple Sclerosis Databases, Factual Multivariate Analysis
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Named entity recognition and classification in biomedical text using classifier ensemble.

International journal of data mining and bioinformatics Jan 1, 2015
Named Entity Recognition and Classification (NERC) is an important task in information extraction for biomedicine domain. Biomedical Named Entities include mentions of proteins, genes, DNA, RNA, etc. which, in general, have complex structures and are...
Computational Biology Support Vector Machine Databases, Genetic Data Mining Humans Algorithms
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Real-time Data Fusion Platforms: The Need of Multi-dimensional Data-driven Research in Biomedical Informatics.

Studies in health technology and informatics Jan 1, 2015
Systems designed to expedite data preprocessing tasks such as data discovery, interpretation, and integration that are required before data analysis drastically impact the pace of biomedical informatics research. Current commercial interactive and re...
Database Management Systems Information Storage and Retrieval Needs Assessment Computer Systems Research Design Computational Biology Databases, Factual Knowledge Bases
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A Review of Computational Intelligence Methods for Eukaryotic Promoter Prediction.

Nucleosides, nucleotides & nucleic acids Jan 1, 2015
In past decades, prediction of genes in DNA sequences has attracted the attention of many researchers but due to its complex structure it is extremely intricate to correctly locate its position. A large number of regulatory regions are present in DNA...
Promoter Regions, Genetic Eukaryota Artificial Intelligence Computational Biology
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Computer-based prediction of mitochondria-targeting peptides.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Computational methods are invaluable when protein sequences, directly derived from genomic data, need functional and structural annotation. Subcellular localization is a feature necessary for understanding the protein role and the compartment where t...
Humans Artificial Intelligence Peptides Genomics Protein Transport Mitochondrial Proteins Models, Biological Computational Biology Mitochondria Internet Datasets as Topic
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Machine learning from concept to clinic: reliable detection of BRAF V600E DNA mutations in thyroid nodules using high-dimensional RNA expression data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2015
The promise of personalized medicine will require rigorously validated molecular diagnostics developed on minimally invasive, clinically relevant samples. Measurement of DNA mutations is increasingly common in clinical settings but only higher-preval...
Biopsy, Fine-Needle DNA, Neoplasm Oligonucleotide Array Sequence Analysis Proto-Oncogene Proteins B-raf RNA, Neoplasm Mutation High-Throughput Nucleotide Sequencing DNA Mutational Analysis Computational Biology Support Vector Machine Humans Machine Learning Gene Expression Profiling Thyroid Nodule
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Advances in protein contact map prediction based on machine learning.

Medicinal chemistry (Shariqah (United Arab Emirates)) Jan 1, 2015
A protein contact map is a simplified, two-dimensional version of the three-dimensional protein structure. Protein contact map is proved to be crucial in forming the three-dimensional structure. Contact map prediction has now become an indispensable ...
Algorithms Computational Biology Proteins Neural Networks, Computer Machine Learning Protein Conformation
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Neural networks and Fuzzy clustering methods for assessing the efficacy of microarray based intrinsic gene signatures in breast cancer classification and the character and relations of identified subtypes.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
In the classification of breast cancer subtypes using microarray data, hierarchical clustering is commonly used. Although this form of clustering shows basic cluster patterns, more needs to be done to investigate the accuracy of clusters as well as t...
Female Breast Neoplasms Gene Expression Profiling Humans Neural Networks, Computer Fuzzy Logic Computational Biology Gene Expression Regulation, Neoplastic Cluster Analysis Oligonucleotide Array Sequence Analysis
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Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...
Tuberculosis Protein Conformation Nerve Net Proteins Models, Biological Humans Neural Networks, Computer Algorithms Drug Discovery Image Processing, Computer-Assisted Computational Biology
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GENN: a GEneral Neural Network for learning tabulated data with examples from protein structure prediction.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
We present a GEneral Neural Network (GENN) for learning trends from existing data and making predictions of unknown information. The main novelty of GENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its...
Proteins Models, Molecular Protein Conformation Neural Networks, Computer Software Computational Biology
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