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We discussed the stability of genetic regulatory networks (GRNs) with multiple time-varying delays. Most of the results about the stability of them are based on the model in which the transcription and translation delays in every gene product take a same value. We generalized the model by a differential equation with multiple time-varying-delays to an extend field. We also considered the sufficient...
Trypanosma brucei (T. Brucei) is an important pathogen agent of African trypanosomiasis. The flagellum is an essential and multifunctional organelle of T. Brucei, thus it is very important to recognize the flagellar proteins from T. Brucei proteins for the purposes of both biological research and drug design. In this paper, we investigate computationally recognizing flagellar proteins in T. Brucei...
Essential proteins are crucial to cellular survival and development. Traditionally, essential proteins are identified by knock-out experiments, which are expensive and often fatal to the target organisms. Regarding this, an important approach to essential protein identification is through computational prediction. In this research, we present a novel computational method, Integrated Edge Weights (IEW),...
Breast cancer is a leading cause of cancer-related deaths in women worldwide. Discovery of breast cancer-related disease genes is becoming very important to researcher and opens a new way to investigate pathogenic mechanism of breast cancer. Many studies have shown that the availability of human genome-wide protein-protein interactions (PPI) provides us with new opportunity for discovering disease-genes...
Disease-causing genes prioritization is very important for understanding mechanisms of diseases and biomedical applications, such as drug design. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease processes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively...
The identification of modules in complex networks is important for the understanding of systems. Recent studies have shown those functional modules can be identified from the protein interaction a network, what's more, the complex modules have not only relatively high density, but also have high coefficient of affinity. However, these analyses are challenging because of the presence of unreliable...
To identify the underlying disease gene of human genetic disorders is a challenging and meaningful task in bioinformatics research. Recently, several methods we re developed based on PPI network, motivated by the observation that the disease genes of the same or similar diseases tend to lie close to each other in the PPI network. However, most of these methods based on the direct neighbors or shortest...
Ionizing radiation has a critical influence on human health In order to explore the correlation between radiation and thymic lymphoid from the signal transduction pathways and to provide a biological basis to further elucidate the radiation carcinogenesis The mouse were irradiated with the X rays (1.75 Gy per time, 1 time per week for consecutive four times, total doses of 7 Gy). The mouse were killed...
This paper presents a comparative study between Partial Least Squares (PLS) method and support vector regression (SVR) in modeling the relationship between the near infrared spectra (NIRS) and the protein contents in Cordyceps militaris mycelia powder samples. Both of the models were optimized by selecting the suitable spectra preprocessing methods and the best modeling parameters. And then the optimum...
Lipoprotein lipase (LPL) of Tianfu meat goose was cloned and sequenced using a RT-PCR approach. The nucleotide sequence covered 468 bp with an open reading frame of 155 amino acids. Alignment analysis indicated that the nucleotide sequences are highly conserved to other species studied including chicken, domestic guinea pig, house mouse, Norway rat, cattle, cow and goat, and the homologies are 92...
Gene expression data possess two main features: small samples and high dimensions. There are many difficulties on analyzing gene expression data using the traditional machine learning methods. In this paper we use an SVM-RFE based method to obtain the set of trait genes that are related to the disease-resistance property in rice and evaluate these genes according to some heuristics. And then we query...
The performance of support vector machines (SVM) drops significantly while facing imbalanced datasets, though it has been extensively studied and has shown remarkable success in many applications. Some researchers have pointed out that it is difficult to avoid such decrease when trying to improve the efficient of SVM on imbalanced datasets by modifying the algorithm itself only. Therefore, as the...
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