The maximum matching graph M(G) of a graph G is a simple graph whose vertices are the maximum matchings of G and where two maximum matchings are adjacent in M(G) if they differ by exactly one edge. In this paper, ...The maximum matching graph M(G) of a graph G is a simple graph whose vertices are the maximum matchings of G and where two maximum matchings are adjacent in M(G) if they differ by exactly one edge. In this paper, we prove that if a graph is isomorphic to its maximum matching graph, then every block of the graph is an odd cycle.展开更多
A connected graph G is said to be a factor-critical graph if G - v has a perfect matching for every vertex v of G. In this paper, the 2-connected factor-critical graph G which has exactly |E(G)|+ 1 maximum matchi...A connected graph G is said to be a factor-critical graph if G - v has a perfect matching for every vertex v of G. In this paper, the 2-connected factor-critical graph G which has exactly |E(G)|+ 1 maximum matchings is characterized.展开更多
The maximum matching graph of a graph has a vertex for each maximummatching and an edge for each pair of maximum matchings which differ by exactly oneedge. In this paper, we prove that the connectivity of maximum matc...The maximum matching graph of a graph has a vertex for each maximummatching and an edge for each pair of maximum matchings which differ by exactly oneedge. In this paper, we prove that the connectivity of maximum matching graph of abipartite graph is equal to its minimum degree.展开更多
Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high...Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data,which make it possible to predict overlapping complexes through computational methods.Research shows that overlapping complexes can contribute to identifying essential proteins,which are necessary for the organism to survive and reproduce,and for life's activities.Scholars pay more attention to the evaluation of protein complexes.However,few of them focus on predicted overlaps.In this paper,an evaluation criterion called overlap maximum matching ratio(OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules.Comparison of essential proteins and gene ontology(GO) analysis are also used to assess the quality of overlaps.We perform a comprehensive comparison of serveral overlapping complexes prediction approaches,using three yeast protein-protein interaction(PPI) networks.We focus on the analysis of overlaps identified by these algorithms.Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.展开更多
Some new concepts of effective incidence matrix,ascending order adjacency matrix andend-result vertex are introduced,and some improvements of the maximum weight matchingalgorithm are made.With this method a computer p...Some new concepts of effective incidence matrix,ascending order adjacency matrix andend-result vertex are introduced,and some improvements of the maximum weight matchingalgorithm are made.With this method a computer program in FORTRAN language is realized onthe computers FELIX C-512 and IBM-PC.Good results are obtained in practical operations.展开更多
Background: The clinical significance of uric acid (UA) in patients with chronic kidney disease (CKD) has never been elucidated in detail. Objectives: The aim of this study was to elucidate the predictive value of hyp...Background: The clinical significance of uric acid (UA) in patients with chronic kidney disease (CKD) has never been elucidated in detail. Objectives: The aim of this study was to elucidate the predictive value of hyperuricemia (HU) in relation to kidney disease progression in CKD patients. Methods: We reviewed data obtained from 201 CKD patients. Renal outcome was assessed by performing the Kaplan-Meier and Cox proportional hazard regression models. The renal outcomes of CKD patients with and without HU were compared by using a propensity score-matched cohort. Results: The results of a multivariate Cox regression analysis showed that HU (UA ≥ 7.1 mg/dL) (P = 0.001), diabetes mellitus (P = 0.003), and a high urine albumin-to-creatinine ratio (P = 0.0005) were significantly associated with a ≥50% eGFR decline or ESRD. The serum UA values were positively correlated with mean blood pressure (P = 0.007), visceral fat area (P = 0.0003), and maximum carotid intima-media thickness (P = 0.0003). The Kaplan-Meier analysis in the propensity score-matched cohort indicated that the renal survival rate of the group of CKD patients with HU was significantly lower than that of the group without HU (log rank, P Conclusion: The results of this study suggest that the serum UA value is a predictor of CKD progression.展开更多
基金Supported by National Natural Science of Foundation of China (Grant Nos. 10531070, 10721101)KJCX YW-S7 of CAS
文摘The maximum matching graph M(G) of a graph G is a simple graph whose vertices are the maximum matchings of G and where two maximum matchings are adjacent in M(G) if they differ by exactly one edge. In this paper, we prove that if a graph is isomorphic to its maximum matching graph, then every block of the graph is an odd cycle.
基金supported by the National Natural Science Foundation of China(No.11551003)the Scientific research fund of the Science and Technology Program of Guangzhou,China(No.201510010265)the Qinghai Province Natural Science Foundation(No.2015-ZJ-911)
文摘A connected graph G is said to be a factor-critical graph if G - v has a perfect matching for every vertex v of G. In this paper, the 2-connected factor-critical graph G which has exactly |E(G)|+ 1 maximum matchings is characterized.
基金This research is suppouted by the National Natural Science Foundation of China(10201019)
文摘The maximum matching graph of a graph has a vertex for each maximummatching and an edge for each pair of maximum matchings which differ by exactly oneedge. In this paper, we prove that the connectivity of maximum matching graph of abipartite graph is equal to its minimum degree.
基金Project supported by the National Scientific Research Foundation of Hunan Province, China (Nos. 14C0096, 10C0408, and 10B010), the Natural Science Foundation of Hunan Province, China (Nos. 13JJ4106 and 14J J3138), and the Science and Technology Plan Project of Hunan Province, China (No. 2010FJ3044)
文摘Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data,which make it possible to predict overlapping complexes through computational methods.Research shows that overlapping complexes can contribute to identifying essential proteins,which are necessary for the organism to survive and reproduce,and for life's activities.Scholars pay more attention to the evaluation of protein complexes.However,few of them focus on predicted overlaps.In this paper,an evaluation criterion called overlap maximum matching ratio(OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules.Comparison of essential proteins and gene ontology(GO) analysis are also used to assess the quality of overlaps.We perform a comprehensive comparison of serveral overlapping complexes prediction approaches,using three yeast protein-protein interaction(PPI) networks.We focus on the analysis of overlaps identified by these algorithms.Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.
文摘Some new concepts of effective incidence matrix,ascending order adjacency matrix andend-result vertex are introduced,and some improvements of the maximum weight matchingalgorithm are made.With this method a computer program in FORTRAN language is realized onthe computers FELIX C-512 and IBM-PC.Good results are obtained in practical operations.
文摘Background: The clinical significance of uric acid (UA) in patients with chronic kidney disease (CKD) has never been elucidated in detail. Objectives: The aim of this study was to elucidate the predictive value of hyperuricemia (HU) in relation to kidney disease progression in CKD patients. Methods: We reviewed data obtained from 201 CKD patients. Renal outcome was assessed by performing the Kaplan-Meier and Cox proportional hazard regression models. The renal outcomes of CKD patients with and without HU were compared by using a propensity score-matched cohort. Results: The results of a multivariate Cox regression analysis showed that HU (UA ≥ 7.1 mg/dL) (P = 0.001), diabetes mellitus (P = 0.003), and a high urine albumin-to-creatinine ratio (P = 0.0005) were significantly associated with a ≥50% eGFR decline or ESRD. The serum UA values were positively correlated with mean blood pressure (P = 0.007), visceral fat area (P = 0.0003), and maximum carotid intima-media thickness (P = 0.0003). The Kaplan-Meier analysis in the propensity score-matched cohort indicated that the renal survival rate of the group of CKD patients with HU was significantly lower than that of the group without HU (log rank, P Conclusion: The results of this study suggest that the serum UA value is a predictor of CKD progression.