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56 papers found.
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TEMs but not DKK1 could serve as complementary biomarkers for AFP in diagnosing AFP-negative hepatocellular carcinoma

administration: Liping Mao, Yueguo Wang. Resources: Shouzhong Fu, Jianxin Wang. Software: Delin Wang, Gang Han. Validation: Shouzhong Fu, Jianxin Wang. Writing ± original draft: Liping Mao. Writing ± review

A scoring system to effectively evaluate central nervous system tuberculosis in patients with miliary tuberculosis

There is currently no convenient way to effectively evaluate whether a miliary tuberculosis patient is complicated with central nervous system (CNS) tuberculosis. We aimed to find such a way by analyzing the clinical data of these patients. Fifty patients with confirmed miliary tuberculosis and 31 patients with confirmed miliary tuberculosis complicated with CNS tuberculosis from ...

CXCL10/IP-10 Neutralization Can Ameliorate Lipopolysaccharide-Induced Acute Respiratory Distress Syndrome in Rats

The role of C-X-C motif chemokine 10 (CXCL10), a pro-inflammatory factor, in the development of acute respiratory distress syndrome (ARDS) remains unclear. In this study, we explored the role of CXCL10 and the effect of CXCL10 neutralization in lipopolysaccharide (LPS)-induced ARDS in rats. The expression of CXCL10 and its receptor chemokine receptor 3(CXCR3) increased after LPS ...

FLEXc: protein flexibility prediction using context-based statistics, predicted structural features, and sequence information

Background The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in ...

Predicting essential proteins based on subcellular localization, orthology and PPI networks

Background Essential proteins play an indispensable role in the cellular survival and development. There have been a series of biological experimental methods for finding essential proteins; however they are time-consuming, expensive and inefficient. In order to overcome the shortcomings of biological experimental methods, many computational methods have been proposed to predict ...

Identification of protein complexes from multi-relationship protein interaction networks

Background Protein complexes play an important role in biological processes. Recent developments in experiments have resulted in the publication of many high-quality, large-scale protein-protein interaction (PPI) datasets, which provide abundant data for computational approaches to the prediction of protein complexes. However, the precision of protein complex prediction still needs ...

APOC3 induces endothelial dysfunction through TNF-α and JAM-1

Background The fatality rate for cardiovascular disease (CVD) has increased in recent years and higher levels of triglyceride have been shown to be an independent risk factor for atherosclerotic CVD. Dysfunction of endothelial cells (ECs) is also a key factor of CVD. APOC3 is an important molecule in lipid metabolism that is closely associated with hyperlipidemia and an increased ...

The thiG Gene Is Required for Full Virulence of Xanthomonas oryzae pv. oryzae by Preventing Cell Aggregation

Bacterial blight of rice is an important serious bacterial diseases of rice in many rice-growing regions, caused by Xanthomonas oryzae pv. oryzae (Xoo). The thiG gene from Xoo strain ZJ173, which is involved with thiazole moiety production in the thiamine biosynthesis pathway, is highly conserved among the members of Xanthomonas. The thiG deletion mutant displayed impaired ...

Rechecking the Centrality-Lethality Rule in the Scope of Protein Subcellular Localization Interaction Networks

Essential proteins are indispensable for living organisms to maintain life activities and play important roles in the studies of pathology, synthetic biology, and drug design. Therefore, besides experiment methods, many computational methods are proposed to identify essential proteins. Based on the centrality-lethality rule, various centrality methods are employed to predict ...

Identifying disease genes by integrating multiple data sources

Background Now multiple types of data are available for identifying disease genes. Those data include gene-disease associations, disease phenotype similarities, protein-protein interactions, pathways, gene expression profiles, etc.. It is believed that integrating different kinds of biological data is an effective method to identify disease genes. Results In this paper, we propose ...

Prediction of disease genes using tissue-specified gene-gene network

Background Tissue specificity is an important aspect of many genetic diseases in the context of genetic disorders as the disorder affects only few tissues. Therefore tissue specificity is important in identifying disease-gene associations. Hence this paper seeks to discuss the impact of using tissue specificity in predicting new disease-gene associations and how to use tissue ...

Disease gene identification by using graph kernels and Markov random fields

Genes associated with similar diseases are often functionally related. This principle is largely supported by many biological data sources, such as disease phenotype similarities, protein complexes, protein-protein interactions, pathways and gene expression profiles. Integrating multiple types of biological data is an effective method to identify disease genes for many genetic ...

Re-alignment of the unmapped reads with base quality score

Motivation Based on the next generation genome sequencing technologies, a variety of biological applications are developed, while alignment is the first step once the sequencing reads are obtained. In recent years, many software tools have been developed to efficiently and accurately align short reads to the reference genome. However, there are still many reads that can't be mapped ...

EPGA: de novo assembly using the distributions of reads and insert size

Motivation: In genome assembly, the primary issue is how to determine upstream and downstream sequence regions of sequence seeds for constructing long contigs or scaffolds. When extending one sequence seed, repetitive regions in the genome always cause multiple feasible extension candidates which increase the difficulty of genome assembly. The universally accepted solution is ...

Identifying essential proteins from active PPI networks constructed with dynamic gene expression

Essential proteins are vitally important for cellular survival and development, and identifying essential proteins is very meaningful research work in the post-genome era. Rapid increase of available protein-protein interaction (PPI) data has made it possible to detect protein essentiality at the network level. A series of centrality measures have been proposed to discover ...

Specificity Protein 1 Transcription Factor Regulates Human ARTS Promoter Activity through Multiple Binding Sites

Apoptosis-related protein in the TGF-β signaling pathway (ARTS) is an unusual mitochondrial Septin-like protein which functions as a tumor suppressor. There are various splice variants derived from the human Septin4 gene, one of which is ARTS, also known as Septin4_i2. Unlike other Septin4 members, ARTS can induce apoptosis in many cells, however, the underlying molecular mechanism ...

Prediction of disease-related genes based on weighted tissue-specific networks by using DNA methylation

Background Predicting disease-related genes is one of the most important tasks in bioinformatics and systems biology. With the advances in high-throughput techniques, a large number of protein-protein interactions are available, which make it possible to identify disease-related genes at the network level. However, network-based identification of disease-related genes is still a ...

Prioritization of orphan disease-causing genes using topological feature and GO similarity between proteins in interaction networks

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease studies. However, it is still time-consuming and laborious to determine the real disease-causing genes by biological experiments. With the advances of the high-throughput techniques, a large number of protein-protein interactions have been produced. Therefore, to ...

Predicting beta-turns in proteins using support vector machines with fractional polynomials

Background β-turns are secondary structure type that have essential role in molecular recognition, protein folding, and stability. They are found to be the most common type of non-repetitive structures since 25% of amino acids in protein structures are situated on them. Their prediction is considered to be one of the crucial problems in bioinformatics and molecular biology, which ...

Detecting protein complexes from active protein interaction networks constructed with dynamic gene expression profiles

Background Protein interaction networks (PINs) are known to be useful to detect protein complexes. However, most available PINs are static, which cannot reflect the dynamic changes in real networks. At present, some researchers have tried to construct dynamic networks by incorporating time-course (dynamic) gene expression data with PINs. However, the inevitable background noise ...