2012 IEEE 6th International Conference on Systems Biology (ISB)最新文献

{"title":"Analysis of morphological evolution in a long-term experiment with Escherichia coli","authors":"F. Cui, B. Yuan","doi":"10.1109/ISB.2012.6314138","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314138","url":null,"abstract":"Great attentions are still paid to the morphological evolution, such as the waiting time to the morphological stability in constant environment, the contributions of different evolutionary forces to the morphological evolution and so on, despite considerable progress. To investigate these issues, some biologists seek to carry out evolution experiments owing to the incompleteness and uncontrollability of the fossil record and the natural populations. We analyze the morphology (cell size) evolution observed from a long-term evolution experiment with Escherichia coli by Lenski et al. and explore these questions more rigorously. We adopt a population genetics model, the Wright-Fisher model, to describe this morphological evolution and calculate the estimates of the waiting time until the ultimate stasis (near stasis) in morphology (cell size) in the long-term experiment by simulations. These calculations have been verified to be in good accordance with the experimental data, which demonstrates the effectiveness of our model. We have shown how the per-locus mutation rate, the average selection advantage per mutation and the population size devote to the morphology (cell size) evolution. Our results indicate that the selective advantage plays a powerful effect on this morphological evolution. By comparison, the mutation rate and population size have a weaker influence.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130379190","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}

{"title":"Analysis of a HBV infection model with non-cytolytic cure process","authors":"X. Zhuo","doi":"10.1109/ISB.2012.6314127","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314127","url":null,"abstract":"Mathematical models have been used to understand the factors that govern infectious disease progression in viral infections. Many models ignore the loss term of free virus particle when it enters the target cell. In this paper, we discuss a virus infection model with the loss term of free virus and the non-cytolytic loss of infected cells. Stable analysis of our model was given. If the basic reproduction number R0 <; 1, the infection-free equilibrium is globally asymptotically stable and the virus is cleared; if the basic reproduction number R0 >; 1, then the virus would persist in the host.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133930875","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}

{"title":"Comparing two models based on the transcriptional regulation by KaiC of cyanobacteria rhythm","authors":"Y. Li, Hui Wu, Jinhuo Luo","doi":"10.1109/ISB.2012.6314139","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314139","url":null,"abstract":"Circadian clocks are self-sustained biological oscillators that can be entrained by environmental cues. Cyanobacteria are the simplest organisms known to exhibit circadian rhythms, which is the fundamental process of homeostasis adapting to daily environmental changes. The cyanobacterial clock gene products, KaiA, KaiB, and KaiC interact with each other, and regulate KaiC phosphorylation and kaiBC expression in a circadian fashion. The total phosphorylation level of KaiC oscillates with a circadian period. In this paper, based on two possible transcriptional regulations, we examined numerically two models, the Transcriptional Activation Model and the Transcriptional Repression Model to generate circadian oscillation of kai genes. These two models both reproduce experimental observed sustained circadian oscillations in constant dark(DD) and constant light(LL). Comparing phase shifts between DD and LL in these two model, the Transcriptional Activation Model is consistent with the experimental observations, suggesting that the Transcriptional Activation Model may reflect the essence of the actual mechanism of kai oscillator in cyanobacteria.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114319593","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}

{"title":"Predicting protein complexes via the integration of multiple biological information","authors":"Xiwei Tang, Jianxin Wang, Yi Pan","doi":"10.1109/ISB.2012.6314132","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314132","url":null,"abstract":"Protein complexes are a cornerstone of many biological processes and together they form various types of molecular machinery that perform a vast array of biological functions. An increase in the amount of protein-protein interaction (PPI) data enables a number of computational methods for predicting protein complexes. There are a mass of algorithms detecting complexes only consider the PPI data. However, the PPI data from high-throughout techniques is flooded with false interactions. In fact, the insufficiency of the PPI data significantly lowers the accuracy of these methods. In the current work, we develop a novel method named CMBI to discover protein complexes via the integration of multiple biological resources including gene expression profiles, essential protein information and PPI data. First, CMBI defines the functional similarity of each pair of interacting proteins based on the edge-clustering coefficient (ECC) from the PPI network and the Pearson correlation coefficient (PCC) from the gene expression data. Second, CMBI selects essential proteins as seeds to bnild the protein complex cores. During the growth process, the seeds' essential protein neighbors and the neighbors whose functional similarity (FS) with the seeds are more than the threshold T will be added to the complex cores. After the complex cores are constructed, CMBI begins to generate protein complexes by attaching their direct neighbors with F S >; T to the cores. In addition to the essential proteins, CMBI also uses other proteins as seeds to expand protein complexes. To check the performance of CMBI, we compare the complexes discovered by CMBI with the ones found by other techniques by matching the predicted complexes against the reference complexes. We use subsequently GO::TermFinder to analyze the complexes predicted by various methods. Finally, the effect of parameter T is investigated. The results from GO functional enrichment and matching analyses show that CMBI performs significantly better than the state-of-the-art methods. It means that it's successful for us to integrate multiple biological information to identify protein complexes in the PPI network.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114606628","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}

{"title":"Functional tunability of biological circuits from tinkers","authors":"Changhong Shi, T. Zhou","doi":"10.1109/ISB.2012.6314114","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314114","url":null,"abstract":"In many complex regulatory networks with interlinked feedback loops, the simple core circuits are sufficient to achieve specific biological functions of the entire networks, naturally raising a question: what is the role of the additional feedback loops. Here, by investigating auto-activation and activator-repressor circuits, two most common functional motifs in regulatory networks, we show that the toggle switch acts as a tinker to elaborate the dynamical behavior of both circuits. Specifically, the additional loop does not significantly affect the stable states of the auto-activation circuit but can tune the stimulation threshold for switch (i.e., the minimal stimulus required to switch the system from the low to the high state). For the activator- repressor circuit, the tinker can tune the stimulation threshold for oscillation (i.e., the bifurcation point to generate oscillations) as well as the oscillation frequency but does not change the oscillation amplitude. These detailed results not only provide guidelines to the engineering of both synthetic circuits but also imply a significant fact that additional loops of the core circuit in a complex network are not really redundant but play a role of tuning the network's function.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128573221","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}

{"title":"ppiPre - an R package for predicting protein-protein interactions","authors":"Yue Deng, Lin Gao","doi":"10.1109/ISB.2012.6314159","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314159","url":null,"abstract":"Since the existing experimental techniques for identifying protein-protein interactions (PPIs) are expensive and time-consuming, and the results are incomplete and/or noisy, developing computational methods for effectively predicting PPIs is of great importance. Therefore, we develop the R package ppiPre, which predicts PPIs using heterogeneous data sources, including Gene Ontology (GO) annotations, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations and topological properties of the PPI network. ppiPre supports up to 20 species and provides useful functions for predicting PPIs and calculating semantic and topological similarities between proteins. ppiPre is open source and freely available from http://cran.r-project.org/web/packages/ppiPre).","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134537967","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}

{"title":"Identifying novel glioma associated pathways based on integrated ‘omics’ data","authors":"Yan-Wei Hu, Jinquan Li, Jiajia Chen, Guang Hu, Bairong Shen","doi":"10.1109/ISB.2012.6314112","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314112","url":null,"abstract":"Microarray represents a high throughput technology for analyzing expression profiles, and thus it has been widely applied in the study of pathogenesis of glioma. However, most of the analyses focused on detecting the differentially expressed genes in glioma. Although it is well accepted that the pathway-derived signatures is more reproducible than that at gene level, few meta-analyses of multiple microarray datasets at system level have been previously performed. In this article, we performed meta-analysis on different published glioma expression profiles and compared the overlapping of signature at gene and pathway level. Pathway enrichment analysis result of GeneGO database and Gene Set Enrichment Analysis (GSEA) showed that 100% and 64% of the similarity was higher than that of genes respectively. Moreover, we integrated other omics data on glioma, such as MicroRNA expression profiles and Chip-Seq data, for further verification. The results showed that the significant signatures of different data sets are more similar at pathway level than at gene level. 12 pathways found by GeneGO database were shared by four stages among several datasets. 5 of these pathways, such as Regulation of epithelial-to-mesenchymal transition (EMT), TGF-beta-dependent induction of EMT via SMADs, were putative novel pathways on glioma and need further experimental verification.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125977457","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}

{"title":"An integrative framework for identifying consistent microRNA expression signatures associated with clear cell renal cell carcinoma","authors":"Jiajia Chen, Daqin Zhang, Wenyu Zhang, Yifei Tang, Lingchuan Guo, Bairong Shen","doi":"10.1109/ISB.2012.6314110","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314110","url":null,"abstract":"Clear cell renal cell carcinoma (ccRCC) is the most common and invasive renal-originated malignancy. Altered microRNA expression has been observed in many human cancers including ccRCC. Microarray is routinely used in labs worldwide for detecting cancer specific microRNA expression profiles, but no consistent conclusion could be drawn so far. The function of microRNAs in carcinogenesis of this tumor type is thereof largely unknown. In this study, we describe an integrative framework to improve the comparability of differentially expressed microRNAs (DE-miRNAs) from different experiments, and apply it to 4 publicly available microRNA expression datasets in ccRCC. The approach uses a novel statistic method for cancer outlier detection. The identified DE-miRNAs are then screened by POMA, an in-house developed predictor, for microRNAs with real regulatory activity in the disease. The proposed framework not only achieves high reproducibility across different datasets but also identifies a consistent set of 12 DE-miRNAs which could be putative biomarkers and therapeutic targets. The targets of DE-miRNAs in each dataset were then mapped to functional databases for enrichment analysis. Both novel and previously characterized microRNA-regulated molecular pathways are identified that are likely to contribute to the pathogenesis of ccRCC. Overlapping comparison suggests that independent ccRCC expression profiles are more consistent at pathway level than that at gene/microRNA level.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128876614","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}

{"title":"Dynamics of coexistence of asexual and sexual reproduction in adaptive landscape","authors":"Shuyun Jiao, Yanbo Wang, P. Ao","doi":"10.1109/ISB.2012.6314135","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314135","url":null,"abstract":"Background: The dynamics for species, especially rare species, with mixed type reproduction is instructive and meaningful for predicting the extinction of them. Though the extinction time is still a difficult problem for sexual or asexual populations. Adaptive landscape introduced by Wright, a powerful concept in systems biology can describe the evolution of organisms. To our knowledge, the dynamical of inhomogenous reproductive organisms have not investigated by a simple model globally. Methods: We describe how a Wright-Fisher process maps to the dynamics of a population with mixed type. We analytically construct adaptive landscape from the general diffusion equation. It shows that the construction is dynamical and the adaptive landscape is independent of the existence and normalization of the stationary distribution. Results: We first give a global model describing the evolution of an inhomogenous reproductive population by adaptive landscape. We visualize the dynamical behavior by adaptive landscape. Finite and infinite potential occur in the process. These results suggest a possible way to investigate the complex reproductive process in an inhomogeneous reproductive population.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127718212","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}

{"title":"A fixed-point blind source extraction algorithm and its application to ECG data analysis","authors":"Hongjuan Zhang, Zikai Wu, Shuxue Ding, Luonan Chen","doi":"10.1109/ISB.2012.6314115","DOIUrl":"https://doi.org/10.1109/ISB.2012.6314115","url":null,"abstract":"Generalized autocorrelations and complexity pursuit are two recently developed methods for extracting interesting component from time series. They are the extensions of projection pursuit to time series data. In this paper, a fixed-point blind source extraction (BSE) algorithm for generalized autocorrelations and complexity pursuit of the desired signals is presented. The fixed-point algorithm inherits the advantages of the well-known FastICA algorithm of ICA, which is very simple, converges fast, and does not need to choose any learning step sizes. Numerical experiments on electrocardiogram (ECG) data indicate its better performance.","PeriodicalId":224011,"journal":{"name":"2012 IEEE 6th International Conference on Systems Biology (ISB)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114267698","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}