AIMC Topic: Computational Biology

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Assessing the effects of data selection and representation on the development of reliable E. coli sigma 70 promoter region predictors.

PloS one
As the number of sequenced bacterial genomes increases, the need for rapid and reliable tools for the annotation of functional elements (e.g., transcriptional regulatory elements) becomes more desirable. Promoters are the key regulatory elements, whi...

Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder.

Computational biology and chemistry
Protein-protein interactions (PPIs) play essential roles in many biological processes. In protein-protein interaction networks, hubs involve in numbers of PPIs and may constitute an important source of drug targets. The intrinsic disorder proteins (I...

State of the art of fuzzy methods for gene regulatory networks inference.

TheScientificWorldJournal
To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence, trough protei...

Improved feature-based prediction of SNPs in human cytochrome P450 enzymes.

Interdisciplinary sciences, computational life sciences
Single nucleotide polymorphisms (SNPs) make up the most common form of mutations in human cytochrome P450 enzymes family, and have the potential to bring with different drug responses or specific diseases in individual patients. Here, based on machin...

miRBoost: boosting support vector machines for microRNA precursor classification.

RNA (New York, N.Y.)
Identification of microRNAs (miRNAs) is an important step toward understanding post-transcriptional gene regulation and miRNA-related pathology. Difficulties in identifying miRNAs through experimental techniques combined with the huge amount of data ...

GRYFUN: a web application for GO term annotation visualization and analysis in protein sets.

PloS one
Functional context for biological sequence is provided in the form of annotations. However, within a group of similar sequences there can be annotation heterogeneity in terms of coverage and specificity. This in turn can introduce issues regarding th...

n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals.

Computers in biology and medicine
This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search...

A fast clustering algorithm for data with a few labeled instances.

Computational intelligence and neuroscience
The diameter of a cluster is the maximum intracluster distance between pairs of instances within the same cluster, and the split of a cluster is the minimum distance between instances within the cluster and instances outside the cluster. Given a few ...

Towards the automatic classification of neurons.

Trends in neurosciences
The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting growth of information about morphological, physiologic...