In this paper, we present a novel semi-supervised technique for finding privacy-sensitive events in clinical text. Unlike traditional semi-supervised methods, we do not require large amounts of unannotated data. Instead, our approach relies on ...

Multiple sclerosis is an appalling disease which destroys the insulatic covers of the connections between neurons, causing disability and death. Its etiology is not yet fully understood and causes remain still unknown; therefore mathematical and ...

Cryo-Electron Microscopy is a biophysical technique that generates volumetric images of macromolecules. Although it is hard to distinguish the backbone from the density map at medium resolutions such as 5-10Å, the location of major secondary structure ...

Small-angle x-ray scattering (SAXS) is an experimental biophysical method used for gaining insight into the structure of large biomolecular complexes. Under appropriate chemical conditions, the information obtained from a SAXS experiment can be equated ...

A β-sheet is composed of multiple β-strands that are stabilized by inter-strand hydrogen bonds. It has been discovered that a β-sheet is right-handed twisted. We have developed a geometrical method to investigate the relationship between the twist of a ...

We propose a Robust Non-negative Matrix Factorization (RNMF) formulation by introducing L₁-norm regularization terms for decomposed factors to cluster noisy biological networks for identification of functional modules. To solve robust NMF, we develop an ...

Examining the bacterial or functional differences between multiple habitats/populations/phenotypes plays an important role in making inferences about the roles that the taxonomy and functional profiles can take on in microbial ecology. It is therefore ...

Proteomics is the study of the structure and behavior of proteins, and one of the primary approaches to protein identification and quantification is through the analysis of Mass Spectrometry (MS) data. This analysis typically involves a series of ...

Detection and quantification of synapses from microscopic images are important for studying functions of neuronal systems. We present a multi-channel co-localization method and the related tool for detecting and counting synapses in immuno-stained ...

Computational methods of inferring regions of noncoding DNA that regulate gene activity are important to efficient biological validation of gene regulatory control. In many cases the available resources may allow for relatively few biological assays to ...

A novel semi-supervised learning approach is proposed to partition metagenomic reads by combining supervised learning method and unsupervised learning method. In this paper, corresponding analytic methods and dedicated simulating studies were conducted ...

Gene expression profiles quantify the expression of thousands of genes simultaneously, providing a snapshot in time of gene expression in a specific tissue. A gene expression profile can be helpful in understanding the association of genes to the ...

Because of the unequivocally fundamental role of SCF ubiquitin ligase in many biological functions within a living cell including regulating DNA repair, cell cycle progression, and inflammation, we have analyzed the role of domain interactions in ...

Exact Circular Pattern Matching (ECPM) problem consists in finding all occurrences of the rotations of a pattern P of length m in a text T of length n. In this paper we present a fast filter-based algorithm for this problem.

Protein-nucleotide interactions play important roles in many biological processes. The goal of our research is to develop computational methods to discovery patterns on protein structures that associated with the affinity and specificity of the protein-...

This research employs an exhaustive search of different attribute selection algorithms in order to provide a more structured approach to learning design for prediction of Alzheimer's clinical dementia rating (CDR).

Massive parallel sequencing of RNA transcripts by the next generation technology (RNA-Seq) is a powerful method of generating critically important data for discovery of structure and function of eukaryotic genes. The transcripts may or may not carry ...

Automated techniques for locating and identifying key biomedical entities such as diseases in biomedical publications have a wide range of applications, including semantic literature indexing, biocuration support and knowledge discovery. Machine ...

In this work we first investigate clustering techniques to identify different molecular subtypes in colorectal cancer based on RPPA protein expression data for 461 tumor samples across 60 proteins. Principal component analysis (PCA) is used to examine ...

Pseudogenes have long been considered to be nonfunctional segments in the genome, but recent studies have provided evidence to support their novel regulatory roles in biological processes. With the growing interests in pseudogene research, scientists ...