Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033126
Qian Ren, X. Zhuo
K-means algorithm is one of the most classic partition algorithms in clustering algorithms. The result obtained by K-means algorithm varies with the choice of the initial clustering centers. Motivated by this, an improved K-means algorithm is proposed based on the Kruskal algorithm, which is famous in graph theory. The procedure of this algorithm is shown as follows: Firstly, the minimum spanning tree (MST) of the clustered objects is obtained by using Kruskal algorithm. Then K-1 edges are deleted based on weights in a descending order. At last, the average values of the objects contained by the k-connected graphs resulting from last two steps are regarded as the initial clustering centers to cluster. Make the improved K-means algorithm used in gene expression data analysis, simulation experiment shows that the improved K-means algorithm has a better clustering effect and higher efficiency than the traditional one.
{"title":"Application of an improved K-means algorithm in gene expression data analysis","authors":"Qian Ren, X. Zhuo","doi":"10.1109/ISB.2011.6033126","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033126","url":null,"abstract":"K-means algorithm is one of the most classic partition algorithms in clustering algorithms. The result obtained by K-means algorithm varies with the choice of the initial clustering centers. Motivated by this, an improved K-means algorithm is proposed based on the Kruskal algorithm, which is famous in graph theory. The procedure of this algorithm is shown as follows: Firstly, the minimum spanning tree (MST) of the clustered objects is obtained by using Kruskal algorithm. Then K-1 edges are deleted based on weights in a descending order. At last, the average values of the objects contained by the k-connected graphs resulting from last two steps are regarded as the initial clustering centers to cluster. Make the improved K-means algorithm used in gene expression data analysis, simulation experiment shows that the improved K-means algorithm has a better clustering effect and higher efficiency than the traditional one.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122536457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033145
Yu-Shu Liu, Chung-Hsaio Chao, Hao-Teng Chang, M. Chang, Yong Wang, Tun-Wen Pai
The signal peptide of eosinophil cationic protein (ECPsp) is known to play an important role in translocating ECP to extracellular space. However, we previously discovered that ECPsp has a novel function of inhibiting microbial growth and regulating the gene expression of tumor growth factor-alpha (TGF-α) and epidermal growth factor receptor (EGFR) in mammalian cells. In the present study, we first generated a DNA microarray dataset, which showed that ECPsp up-regulated inflammatory molecules including cytokines, chemokines, interferon-induced molecules, and Toll-like receptors. We then generated a function linkage network by integrating the microarray dataset with the KEGG pathway database, and discovered that STAT1, an important factor regulating cytokine expression and release, served as a hub to connect the pathways of cytokine stimulation (TGF-α and EGFR) and inflammatory responses. Furthermore, integrating the ECPsp interactome dataset with the functional linkage network elucidated that STAT1 served as a hub to connect 3 functional clusters, including cell proliferation and survival, protein translational regulation, and inflammatory responses. Our approach involving experimental and computational systems biology provided predicted pathways and potential regulation for further characterization of the novel function of ECPsp under inflammatory conditions.
{"title":"Analysis of gene expression profile triggered by signal peptide of eosinophil cationic protein","authors":"Yu-Shu Liu, Chung-Hsaio Chao, Hao-Teng Chang, M. Chang, Yong Wang, Tun-Wen Pai","doi":"10.1109/ISB.2011.6033145","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033145","url":null,"abstract":"The signal peptide of eosinophil cationic protein (ECPsp) is known to play an important role in translocating ECP to extracellular space. However, we previously discovered that ECPsp has a novel function of inhibiting microbial growth and regulating the gene expression of tumor growth factor-alpha (TGF-α) and epidermal growth factor receptor (EGFR) in mammalian cells. In the present study, we first generated a DNA microarray dataset, which showed that ECPsp up-regulated inflammatory molecules including cytokines, chemokines, interferon-induced molecules, and Toll-like receptors. We then generated a function linkage network by integrating the microarray dataset with the KEGG pathway database, and discovered that STAT1, an important factor regulating cytokine expression and release, served as a hub to connect the pathways of cytokine stimulation (TGF-α and EGFR) and inflammatory responses. Furthermore, integrating the ECPsp interactome dataset with the functional linkage network elucidated that STAT1 served as a hub to connect 3 functional clusters, including cell proliferation and survival, protein translational regulation, and inflammatory responses. Our approach involving experimental and computational systems biology provided predicted pathways and potential regulation for further characterization of the novel function of ECPsp under inflammatory conditions.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125844492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033169
Min Wang, Guangfeng Kan, Cuijuan Shi, Qiuju Xie, Yingying Huang, Zhenhuan Lei
Under the heavy metal polluted circumstances, microorganisms certainly have some changes in terms of species, quantity, community structure and diversity to adapt the environments. Now, many heavy metal tolerant microbe groups have been studied. In the study, a heavy metal tolerant and psychrophilic bacterium strain from Antarctica was screened. Based on 16S rDNA sequence analysis, this strain belongs to Planococcus, named as Planococcus sp. O5. The capacity of antimetal of Planococcus sp. O5 is Pb2+ > Cu2+ > Hg2+ > Cd2+ > Zn2+, and the MICs is 320 mg/L, 130 mg/L, 80 mg/L, 80 mg/L and 40 mg/L, respectively. Lipid peroxidation (indicated by malonydialdehyde content) happened in strain O5 induced with Cu2+. At the same time, the antioxidation enzyme activity (such as SOD, POD and CAT) had stimulus-controlled improvement, which is a certain protection against heavy metals. Therefore, as an important feature adapting the stress environments, the activity of antimetal, can reflect the adaptive strategy of microorganism to some extent. This paper studied the activity of antimetal and antioxidation of a bacterial strain, which can help us better understand the bacteria how to adapt the extreme environments.
{"title":"Heavy metal tolerance of an antarctic bacterial Strain O5 and its antioxidant enzyme activity changes induced by Cu2+","authors":"Min Wang, Guangfeng Kan, Cuijuan Shi, Qiuju Xie, Yingying Huang, Zhenhuan Lei","doi":"10.1109/ISB.2011.6033169","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033169","url":null,"abstract":"Under the heavy metal polluted circumstances, microorganisms certainly have some changes in terms of species, quantity, community structure and diversity to adapt the environments. Now, many heavy metal tolerant microbe groups have been studied. In the study, a heavy metal tolerant and psychrophilic bacterium strain from Antarctica was screened. Based on 16S rDNA sequence analysis, this strain belongs to Planococcus, named as Planococcus sp. O5. The capacity of antimetal of Planococcus sp. O5 is Pb2+ > Cu2+ > Hg2+ > Cd2+ > Zn2+, and the MICs is 320 mg/L, 130 mg/L, 80 mg/L, 80 mg/L and 40 mg/L, respectively. Lipid peroxidation (indicated by malonydialdehyde content) happened in strain O5 induced with Cu2+. At the same time, the antioxidation enzyme activity (such as SOD, POD and CAT) had stimulus-controlled improvement, which is a certain protection against heavy metals. Therefore, as an important feature adapting the stress environments, the activity of antimetal, can reflect the adaptive strategy of microorganism to some extent. This paper studied the activity of antimetal and antioxidation of a bacterial strain, which can help us better understand the bacteria how to adapt the extreme environments.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125986318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033165
X. Chen, W. Ching
In this paper we study the problem of finding optimal control policy for probabilistic Boolean networks (PBNs). Previous works have been done by using dynamic programming-based (DP) method. However, due to the high computational complexity of PBNs, DP method is computationally inefficient for large networks. Inspired by the state reduction strategies studied in [10], we consider using dynamic programming in conjunction with state reduction approach to reduce the computational cost of DP method. Numerical examples are given to demonstrate the efficiency of our proposed method.
{"title":"Finding optimal control policy by using dynamic programming in conjunction with state reduction","authors":"X. Chen, W. Ching","doi":"10.1109/ISB.2011.6033165","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033165","url":null,"abstract":"In this paper we study the problem of finding optimal control policy for probabilistic Boolean networks (PBNs). Previous works have been done by using dynamic programming-based (DP) method. However, due to the high computational complexity of PBNs, DP method is computationally inefficient for large networks. Inspired by the state reduction strategies studied in [10], we consider using dynamic programming in conjunction with state reduction approach to reduce the computational cost of DP method. Numerical examples are given to demonstrate the efficiency of our proposed method.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130423053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033128
Zilong Liu, Wenli Liu, Rui Chen, Yu Wang, N. Liao
Biology image is a main approach of biology research, So the measurement and recognition accurately of biology image, especially the monometer image like cell image, is very important and critical. All these depend on the accurate display of biology image. A key model of standard display function(SDF) for biology image is established at cell level, and measurement images are calibrated by the metrology standard of image using this model. The biology image can be appeared more “true” through this calibration. The SDF of several serial image data at key wavelengths are calibrated using the model, and then these serial data are combined in one image, thus the calibration is achieved. A kind of human erythrocyte image is measured and calibrated correspondly. After calibrated, the chromatism of this image is improved by 3 and the luminance contrast of that is improved by 2.
{"title":"The calibration method research for biology image","authors":"Zilong Liu, Wenli Liu, Rui Chen, Yu Wang, N. Liao","doi":"10.1109/ISB.2011.6033128","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033128","url":null,"abstract":"Biology image is a main approach of biology research, So the measurement and recognition accurately of biology image, especially the monometer image like cell image, is very important and critical. All these depend on the accurate display of biology image. A key model of standard display function(SDF) for biology image is established at cell level, and measurement images are calibrated by the metrology standard of image using this model. The biology image can be appeared more “true” through this calibration. The SDF of several serial image data at key wavelengths are calibrated using the model, and then these serial data are combined in one image, thus the calibration is achieved. A kind of human erythrocyte image is measured and calibrated correspondly. After calibrated, the chromatism of this image is improved by 3 and the luminance contrast of that is improved by 2.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127270022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many networks are proved to have community structure. Dense communities have been intensively investigated in recent years, oppositely seldom attention has been paid to sparse ones, which refer to those communities induced by low or middle-degree nodes rather than high-degree components. Recently, it has gradually been recognized that sparse community is also an important structure in biological networks because most disease genes and drug targets are within it. In this paper, we propose a dynamical method to extract sparse communities in complex networks by constructing local synchronization properties of phase oscillators. Compared to dense communities, sparse ones provide more general building and functional blocks in the networks without emphasis on the dominance of internal degrees over outside ones as well as the constraints of high degree connectors.
{"title":"A dynamical method to extract communities induced by low or middle-degree nodes","authors":"Junhua Zhang, Zhiping Liu, Xiang-Sun Zhang, Luonan Chen","doi":"10.1109/ISB.2011.6033175","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033175","url":null,"abstract":"Many networks are proved to have community structure. Dense communities have been intensively investigated in recent years, oppositely seldom attention has been paid to sparse ones, which refer to those communities induced by low or middle-degree nodes rather than high-degree components. Recently, it has gradually been recognized that sparse community is also an important structure in biological networks because most disease genes and drug targets are within it. In this paper, we propose a dynamical method to extract sparse communities in complex networks by constructing local synchronization properties of phase oscillators. Compared to dense communities, sparse ones provide more general building and functional blocks in the networks without emphasis on the dominance of internal degrees over outside ones as well as the constraints of high degree connectors.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"281 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127479369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033163
Yongmei Su, L. Min
Mathematical models have been used to understand the factors that govern infectious disease progression in viral infections. Many HBV models were based on the basic virus infection model with bilinear mass action incidence of virus and the uninfected target cells introduced by Zeuzem et al. and Nowak et al. But Lequan Min et al. have set up another basic virus infection model with a standard incidence function. In this paper, base on the standard mass action incidence, an adefovir anti-HBV therapy model with time-delay immune response were set up. The globally asymptotically stable analysis of the infection-free equilibrium were given in the paper, for the endemic equilibrium, simulation shows there exist a stable switch. The simulation based on the clinical adefovir therapy data were also given.
{"title":"Stability analysis and simulation of an anti-HBV therapy mathematical model with time-delay immune response","authors":"Yongmei Su, L. Min","doi":"10.1109/ISB.2011.6033163","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033163","url":null,"abstract":"Mathematical models have been used to understand the factors that govern infectious disease progression in viral infections. Many HBV models were based on the basic virus infection model with bilinear mass action incidence of virus and the uninfected target cells introduced by Zeuzem et al. and Nowak et al. But Lequan Min et al. have set up another basic virus infection model with a standard incidence function. In this paper, base on the standard mass action incidence, an adefovir anti-HBV therapy model with time-delay immune response were set up. The globally asymptotically stable analysis of the infection-free equilibrium were given in the paper, for the endemic equilibrium, simulation shows there exist a stable switch. The simulation based on the clinical adefovir therapy data were also given.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123503633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033167
M. Kamada, M. Hayashida, Jiangning Song, T. Akutsu
Understanding of interactions of proteins is important to reveal networks and functions of molecules. Many investigations have been conducted to analyze interactions and contacts between residues. It is supported that residues at interacting sites have co-evolved with those at the corresponding residues in the partner protein to keep the interactions between the proteins. Therefore, mutual information (MI) between residues calculated from multiple sequence alignments of homologous proteins is considered to be useful for identifying contact residues in interacting proteins. In our previous work, we proposed a prediction method for protein-protein interactions using mutual information and conditional random fields (CRFs), and confirmed its usefulness. The discriminative random field (DRF) is a special type of CRFs, and can recognize some specific characteristic regions in an image. Since the matrix consisted of mutual information between residues in two interacting proteins can be regarded as an image, we propose a prediction method for protein residue contacts using DRF models with mutual information. To validate our method, we perform computational experiments for several interactions between Pfam domains. The results suggest that the proposed DRF-based method with MI is useful for predicting protein residue contacts compared with that using the corresponding Markov random field (MRF) model.
了解蛋白质的相互作用对揭示分子的网络和功能具有重要意义。已经进行了许多研究来分析残留物之间的相互作用和接触。相互作用位点的残基与伴侣蛋白中相应残基的残基共同进化，以保持蛋白质之间的相互作用。因此，从同源蛋白的多个序列比对中计算出的残基之间的互信息(MI)被认为对鉴定相互作用蛋白中的接触残基是有用的。在我们之前的工作中，我们提出了一种利用互信息和条件随机场(CRFs)预测蛋白质-蛋白质相互作用的方法，并证实了它的实用性。判别随机场(discriminative random field, DRF)是一种特殊类型的随机场，它可以识别图像中特定的特征区域。由于两个相互作用蛋白残基间互信息构成的矩阵可以看作是一幅图像，我们提出了一种基于互信息的DRF模型的蛋白残基接触预测方法。为了验证我们的方法，我们对Pfam域之间的几个相互作用进行了计算实验。结果表明，与使用相应的马尔可夫随机场(MRF)模型相比，所提出的基于drf的MI方法可用于预测蛋白质残基接触。
{"title":"Discriminative random field approach to prediction of protein residue contacts","authors":"M. Kamada, M. Hayashida, Jiangning Song, T. Akutsu","doi":"10.1109/ISB.2011.6033167","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033167","url":null,"abstract":"Understanding of interactions of proteins is important to reveal networks and functions of molecules. Many investigations have been conducted to analyze interactions and contacts between residues. It is supported that residues at interacting sites have co-evolved with those at the corresponding residues in the partner protein to keep the interactions between the proteins. Therefore, mutual information (MI) between residues calculated from multiple sequence alignments of homologous proteins is considered to be useful for identifying contact residues in interacting proteins. In our previous work, we proposed a prediction method for protein-protein interactions using mutual information and conditional random fields (CRFs), and confirmed its usefulness. The discriminative random field (DRF) is a special type of CRFs, and can recognize some specific characteristic regions in an image. Since the matrix consisted of mutual information between residues in two interacting proteins can be regarded as an image, we propose a prediction method for protein residue contacts using DRF models with mutual information. To validate our method, we perform computational experiments for several interactions between Pfam domains. The results suggest that the proposed DRF-based method with MI is useful for predicting protein residue contacts compared with that using the corresponding Markov random field (MRF) model.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123212019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033174
Ruiqi ang, Kaihui Liu, Luonan Chen
In the developing nervous system, the expression of proneural genes, i.e., Hes1, Neurogenin-2 (Ngn2), and Deltalike-1 (Dll1), oscillates in neural progenitors with a period of 2–3 h, but is persistent in postmitotic neurons. In this paper, we present a computational model for neural fate decisions based on intertwined Notch-Delta signaling involving the Hes1, Notch, and Dll1 proteins. In agreement with experimental observations, the model predicts that Notch-Delta signaling plays critical roles in regulating the choice between remaining as a progenitor and embarking on neural differentiation.
{"title":"Neural fate decisions mediated by notch-delta signaling","authors":"Ruiqi ang, Kaihui Liu, Luonan Chen","doi":"10.1109/ISB.2011.6033174","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033174","url":null,"abstract":"In the developing nervous system, the expression of proneural genes, i.e., Hes1, Neurogenin-2 (Ngn2), and Deltalike-1 (Dll1), oscillates in neural progenitors with a period of 2–3 h, but is persistent in postmitotic neurons. In this paper, we present a computational model for neural fate decisions based on intertwined Notch-Delta signaling involving the Hes1, Notch, and Dll1 proteins. In agreement with experimental observations, the model predicts that Notch-Delta signaling plays critical roles in regulating the choice between remaining as a progenitor and embarking on neural differentiation.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131199745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-03DOI: 10.1109/ISB.2011.6033130
Guanying Piao, Bangguo Qian, Shigeru Saito, Zhiping Liu, Tao Zeng, Yong Wang, Jiarui Wu, Huarong Zhou, Luonan Chen, K. Horimoto
In general, molecular signatures of diseases are estimated by comparing the two sets of molecular data measured for the samples with distinctive phenotypes, and then molecular functions of the diseases are characterized by the following analyses of the signatures. Unfortunately, ambiguous relationships between molecular signatures and functions are observed in some cases, due to a posteriori justification from molecular level to phenotype level. Here, we propose a method for detecting molecular functions of the disease by a deductive justification from phenotype level to molecular level, and illustrate its performance by applying our method to the gene expression and phenotype data sets for diabetes progression in Goto-Kakizaki rat. By our method, the functions identified by the previous studies were well covered, and furthermore, some implications for molecular mechanisms were obtained. Our phenotype-difference oriented method provides some clues to bridge directly a gap between molecular signatures and phenotype data in diabetes.
{"title":"Phenotype-difference oriented identification of molecular functions for diabetes progression in Goto-Kakizaki rat","authors":"Guanying Piao, Bangguo Qian, Shigeru Saito, Zhiping Liu, Tao Zeng, Yong Wang, Jiarui Wu, Huarong Zhou, Luonan Chen, K. Horimoto","doi":"10.1109/ISB.2011.6033130","DOIUrl":"https://doi.org/10.1109/ISB.2011.6033130","url":null,"abstract":"In general, molecular signatures of diseases are estimated by comparing the two sets of molecular data measured for the samples with distinctive phenotypes, and then molecular functions of the diseases are characterized by the following analyses of the signatures. Unfortunately, ambiguous relationships between molecular signatures and functions are observed in some cases, due to a posteriori justification from molecular level to phenotype level. Here, we propose a method for detecting molecular functions of the disease by a deductive justification from phenotype level to molecular level, and illustrate its performance by applying our method to the gene expression and phenotype data sets for diabetes progression in Goto-Kakizaki rat. By our method, the functions identified by the previous studies were well covered, and furthermore, some implications for molecular mechanisms were obtained. Our phenotype-difference oriented method provides some clues to bridge directly a gap between molecular signatures and phenotype data in diabetes.","PeriodicalId":355056,"journal":{"name":"2011 IEEE International Conference on Systems Biology (ISB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133998979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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