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Multiple linear regression (MLR) models were constructed to explain the bitter taste of di‐ and tripeptides based on their chemical nature (structure). Sequences (51 di‐ and 51 tripeptides) were derived from the BIOPEP‐UWM database of sensory peptides and amino acids. The measure of their bitterness was Rcaf., that is, bitterness relative to that of 1 mM caffeine solution (Rcaf. = 1.0). The variables...
A large number of long non-coding RNAs (lncRNAs) have been identified over the past decades. Accumulating evidence proves that lncRNAs play key roles in various biological processes. However, the majority of the lncRNAs have not been functionally characterized. The annotation of lncRNA functions has become an area of focus in the fields of biology and bioinformatics. In this paper, we develop a global...
The collaborations of the diseases might be the key to understand the mechanism of the diseases since it is difficult to detect the role of complex genes and micro RNA in diseases. With the rapid development of technology, several metabolites of many kinds of diseases could be obtained by the advanced machines. Some diseases are related to several metabolites, and some metabolites have strong relationship...
Despite the linear relation between the number of observed spectra and the searching time, the current protein search engines, even the parallel versions, could take several hours to search a large amount of MS/MS spectra, which can be generated in a short time. After a laborious searching process, some (and at times, majority) of the observed spectra are labeled as non-identifiable. We evaluate the...
Discovering similar diseases is very helpful for revealing the pathogenesis of diseases and making direction in drug use. And related diseases are often triggered by disease-related genes. Therefore, function interaction networks structured by disease-related genes are suitable for measurement of disease similarity, and some methods have utilized the advantage of function interaction of disease-related...
Gene ontology (GO) defines terms and classes used to describe gene functions and relationships between them. GO has been the standard to describing the functions of specific genes in different model organisms. GO annotation which tags genes with GO terms has mostly been a manual and timeconsuming curation process. In this paper we describe the development and evaluation of an innovative predictive...
A significant part of our knowledge is relationships between two terms. However, most of these information is documented as unstructured text in various forms, like books, online articles and webpages. Extract those information and store them in a structured database could help people utilize these information more conveniently. In this study, we proposed a novel approach to extract the relationships...
Network pharmacology which is based on bioinformatics and system biology knowledge has been employed into the field of Traditional Chinese Medicine (TCM) researches in recent years. In order to summarize current available bioinformatics databases, especially those can be used for TCM formulae study; a systematic search of Chinese literature by May 2017 was conducted. Results showed that research methods...
We propose a novel, semantic-reasoning-based approach to look for potentially adverse drug-drug interactions (DDIs) by using a knowledge-base of biomedical public ontologies and datasets in a semantic graph representation. This approach makes it possible to find previously unknown relations between different biological entities like drugs, proteins and biological processes, and perform inferences...
The rapid increase in available protein structure datasets requires new techniques for fast, yet, effective analysis of protein 3D structures. In this work, we propose a structure-based signature for protein families, suitable for rapid analysis of multidomain domain protein structures. Our method is alignment-free, using protein strings as the basic representation. A key novelty is the two-stage...
The diversity of the available protein search engines with respect to the utilized matching algorithms, the low overlap ratios among their results and the disparity of their coverage encourage the community of proteomics to utilize ensemble solutions of different search engines. The advancing in cloud computing technology and the availability of distributed processing clusters can also provide support...
Merkel Cell Polyomavirus (MCV) is associated with more than 80% of Merkel cell carcinoma (MCC), a rare but highly lethal form of skin cancer. We made use of the immunological data on MCV available through publications and databases and constructed MCV T cell Antigen Database (MCVdb). MCVdb contains 734 curated antigen entries of MCV antigenic proteins and 30 experimentally verified T cell epitopes...
Gene (microRNA) identification is a key step in understanding the cellular mechanisms. Compared with biological experiments, computational prediction of disease genes is cheaper and more effortless. In this study, we analyzed the properties of tumor-associated microRNA in mouse and found that tumor-associated genes display 8distinguishingfeatures when compared with genes not yet known to be involved...
Recent advances in sequencing allow the study of all identified human genes (≈ 22,000 protein encoding genes), which have differential expression between tissues. However, current knowledge on gene interactions lags behind, especially when one of the elements encodes a mitochondrial protein (≈ 1500). Mitochondrial proteins are encoded either by mitochondrial DNA (mtDNA; 13 proteins) or by nuclear...
Proteins interact with each other to regulate their functionality and localization. The accumulated protein interaction evidences are represented by protein interaction network using a graph abstraction. Topological properties of protein interaction networks have been explored to characterize proteins and predict undiscovered interactions. Meanwhile, many researchers have tried to explain how protein...
Recent studies show that drug-disease associations provide important information for drug discovery and drug repositioning. Wet experimental identification of drug-disease associations is time-consuming and labor-intensive. Therefore, the development of computational methods that predict drug-disease associations is an urgent task. In this paper, we propose a novel computational method named NTSIM,...
A thorough literature research is usually the first step when dealing with a novel topic in science. Regarding the medical domain, a popular starting point for this task is the web based search engine PubMed, which has an index of over 27 million medical publications from the MEDLINE database and other sources. Given certain search terms of interest, e.g. neurodegeneration or the drug FTY 720, results...
With the development of next-generation sequencing technologies, large number of transcripts has been accumulated in public databases. Long non-coding RNAs (lncRNAs), typically above 200 nucleotides in sequence length, have recently attracted increasing interests because of their important roles in various cellular processes. While it is straightforward to distinguishing lncRNAs from most small non-coding...
This study extracted differentially expressed genes (DEG) from a RNA-Seq gene expression experiment of human red blood cells for both case and control. A protein interaction network (PIN) for the DEG at the red blood stage was extracted from protein interaction database. From the protein interaction network built, we identified 64 protein complexes using the molecular complex detection (MCODE) algorithm...
In biology, text-mining is widely used to extract relationships between biological entities. Gene prioritization is also important to analyze diseases, because mutated or dysregulated genes play an important role in pathogenesis. Here, we propose a method to identify disease-related genes using seed genes and network analysis. We constructed an integrating gene network for lung cancer by combining...
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