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Rheumatoid arthritis (RA) is an autoimmune disease that results in a chronic, systemic inflammatory disorder that may affect many tissues and organs, but principally attacks flexible (synovial) joints. Traditional Chinese medicine (TCM) treats RA with herbal formulae according to different syndrome/pattern classification. One important syndrome/pattern in RA is Feng-Han-Shi-Bi. Targeting this syndrome,...
Prediction of protein complexes from proteinprotein interaction (PPI) networks is crucial to unraveling the principles of cellular organization. Most existing approaches only exploit high-throughput experimental PPI data to predict protein complexes. In this paper, we integrate the multiple biomedical resources for protein complex prediction by constructing attributed PPI networks, which include high-throughput...
In protein subcellular localization prediction, a predominant scenario is that the number of available features is much larger than the number of data samples. Among the large number of features, many of them may contain redundant or irrelevant information, causing the prediction systems suffer from overfitting. To address this problem, this paper proposes a dimensionality-reduction method that applies...
Allergy, a hypersensitivity disorder of the immune system, is one of the steadily increasing health problems in the world. Usage of transgenic food products is constantly increasing and hence assessment of product for potential allergenicity is necessary before they are introduced into the human food chain. Though several bioinformatics approach exists for allergen prediction, discriminating the allergen-like...
With the development of high-throughput technique, protein-protein interactions (PPIs) are increasing fast and available conveniently, which make it possible to identify protein complexes in PPI networkf 1–7]. Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks[8–9], which requires protein complex detection methods can identify both...
A signaling pathway, which is represented as a chain of interacting proteins for a biological process, can be predicted from protein-protein interaction (PPI) networks. However, pathway prediction is computationally challenging because of (1) inefficiency in searching all possible paths from the large-scale PPI networks and (2) unreliability of current PPI data generated by automated high-throughput...
We developed a new sparse multivariate regression method, collaborative sparse reduced rank regression(C-sRRR) for detecting genetic networks associated with brain functional networks in schizophrenia (SZ). Our study: 1) introduced both genetic and brain network structure to group single nucleotide polymorphism (SNP) and voxels simultaneously for utilizing the interacting effects implied in both features;...
In silico prediction of drug side-effects in early stage of drug development is becoming more popular now days, which not only reduces the time for drug design but also reduces the drug development costs. In this article we propose an ensemble approach to predict drug side-effects of drug molecules based on their chemical structure. Our idea originates from the observation that similar drugs have...
This paper introduces an approach of using the genetic algorithm for orienting protein-protein interaction networks (PPIs) and discovering pathways. Biological pathways such as metabolic or signaling ones play an important role in understanding cell activities and evolution. A cost-effective method to discover such pathways is analyzing accumulated information about protein-protein interactions, which...
We propose a pairwise protein structure alignment approach based on a joint similarity measure of multiple protein attributes. We map information on a protein's sequence location, structure and characteristic properties onto a highly-localized three-dimensional Gaussian waveform. By allowing the waveform to undergo unique transformations in the time-frequency plane, we allocate distinct parameters...
Recently nonnegative matrix factorization (NMF) has become a popular dimension reduction method and it has been successfully applied to image processing and pattern recognition. In this paper, we propose an incremental locality preserving nonnegative matrix factorization (ILPNMF) method, which is aimed to discover the manifold structure embedded in high-dimensional space that deals well with large...
Proteomics is currently driven by mass spectrometry. For the analysis of tandem mass spectra many computational algorithms have been proposed. There are two approaches, one which assigns a peptide sequence to a tandem mass spectrum directly and one which employs a sequence database for looking up possible solutions. The former method needs high quality spectra while the latter can tolerate lower quality...
Severe acute respiratory syndrome (SARS) is a serious form of pneumonia which results in acute respiratory distress and sometimes death. In this study, we applied the reverse vaccinology approach to determine the antigenic determinant sites present on the protein. The method incorporates the prediction of antigenic sites, solvent accessible region and secondary structure, B-cell epitope prediction,...
One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies...
Decoding protein-DNA interactions is important to understanding gene regulation and has been investigated by worldwide scientists for a long time. However, many aspects of the interactions still need to be uncovered. The crystal structures of protein-DNA complexes reveal detailed atomic interactions between the proteins and DNA and are an excellent resource for investigating the interactions. In this...
Phosphorylation is a post-translational modification process mediated by kinases through the addition of a covalently bound phosphate group, which plays important roles in a wide range of cellular progresses, such as signaling cascades and development. Over the past years, despite many phosphorylation sites have been determined with mass spectrometry techniques, it is not clear which kinase phosphorylates...
Rheumatoid arthritis (RA) is a chronic disease that affects the joints, often those in a person's wrists, fingers, and feet. In contrast to FDA-approved anti-RA drugs, Tripterygium wilfordii Hook F (TwHF), a traditional Chinese medicine (TCM), featured as multi-targeting, have been acknowledged with notable anti-RA effects although the pharmacology is unclear. In this work, we investigated the therapeutic...
Chinese herbs always have activity on multiple targets. For the identification of potential anti-inflammatory compounds from Chinese herbs, six targets, which are mostly associated with inflammatory, were selected as following: Cox-2 (cyclooxygenase 2), PDE4B (phosphodiesterase 4B), p38α MAPK (p38α mitogen-activated protein kinase), JNK3 (c-Jun N-terminal kinases 3), ICE (interlenkin-1β converting...
Proteins are essential parts of our life and participate in virtually every process within a cell. The understanding of protein structures is vital to determine the function of a protein. Protein structure prediction (PSP) from amino acid sequence is one of the high focus problems in bioinformatics today. This is due to the fact that the biological function of the protein is determined by its three...
Three-dimensional (3-D) protein structure determination has become an important area of research in structural bioinformatics. Proteins are responsible for the execution of different functions in the cell. Understanding the 3-D structure provides important information about the protein function. Many computational methodologies for the protein structure prediction were developed along the last 20...
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