Pub Date : 2014-12-18DOI: 10.1109/ISB.2014.6990425
Dayun Wu, Yongmei Su
In this paper, we investigate a class of virus dynamics model with intracellular delay and nonlinear infection rate of saturated functional response. The basic reproduction number R0 for the viral infection is derived, and the global dynamics behavior are completely determined by R0. By constructing suitable Lyapunov functional and using LaSalle invariant principle for the delay differential equations, we find when R0 ≤ 1, the infection-free equilibrium is globally asymptotically stable, and when R0 > 1, the infection equilibrium is also globally asymptotically stable.
{"title":"Dynamical behaviour of a delay differential equation of Hepatitis B virus","authors":"Dayun Wu, Yongmei Su","doi":"10.1109/ISB.2014.6990425","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990425","url":null,"abstract":"In this paper, we investigate a class of virus dynamics model with intracellular delay and nonlinear infection rate of saturated functional response. The basic reproduction number R0 for the viral infection is derived, and the global dynamics behavior are completely determined by R0. By constructing suitable Lyapunov functional and using LaSalle invariant principle for the delay differential equations, we find when R0 ≤ 1, the infection-free equilibrium is globally asymptotically stable, and when R0 > 1, the infection equilibrium is also globally asymptotically stable.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121087837","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990742
Somrak Numnark, S. Ingsriswang, D. Wichadakul
To exploit social media data in vaccine-related areas, we proposed VaccineWatch, a monitoring system with visualizations and analytics of significant vaccine information from Twitter and RSS feeds. The system was designed and implemented as a web application with following distinguished features. First, it comes with graphical user interfaces that visualize perspectives of vaccine-related information mined from social media data. Second, it provides a set of filters allowing users to focus on their diseases, vaccines, countries, and/or companies of interest. Third, it includes the helper tools for the management of social media data collection and backend processes such as Twitter and RSS crawlers. The prototype of VaccineWatch is available at www.vacciknowlogy .org/VaccineWatch.
{"title":"VaccineWatch: a monitoring system of vaccine messages from social media data","authors":"Somrak Numnark, S. Ingsriswang, D. Wichadakul","doi":"10.1109/ISB.2014.6990742","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990742","url":null,"abstract":"To exploit social media data in vaccine-related areas, we proposed VaccineWatch, a monitoring system with visualizations and analytics of significant vaccine information from Twitter and RSS feeds. The system was designed and implemented as a web application with following distinguished features. First, it comes with graphical user interfaces that visualize perspectives of vaccine-related information mined from social media data. Second, it provides a set of filters allowing users to focus on their diseases, vaccines, countries, and/or companies of interest. Third, it includes the helper tools for the management of social media data collection and backend processes such as Twitter and RSS crawlers. The prototype of VaccineWatch is available at www.vacciknowlogy .org/VaccineWatch.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116027258","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990744
R. De, S. Verma, M. Holmes, F. Asselbergs, J. Moore, B. Keating, M. Ritchie, D. Gilbert-Diamond
Despite heritability estimates of 40-70% for obesity, less than 2% of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. Using genotypic data from 18,686 individuals across five study cohorts - ARIC, CARDIA, FHS, CHS, MESA - we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of obesity. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects nonlinear interactions in the context of a quantitative trait. We identified seven novel, epistatic models with a Bonferroni corrected p-value of association <; 0.06. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.
{"title":"Dissecting the obesity disease landscape: Identifying gene-gene interactions that are highly associated with body mass index","authors":"R. De, S. Verma, M. Holmes, F. Asselbergs, J. Moore, B. Keating, M. Ritchie, D. Gilbert-Diamond","doi":"10.1109/ISB.2014.6990744","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990744","url":null,"abstract":"Despite heritability estimates of 40-70% for obesity, less than 2% of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. Using genotypic data from 18,686 individuals across five study cohorts - ARIC, CARDIA, FHS, CHS, MESA - we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of obesity. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects nonlinear interactions in the context of a quantitative trait. We identified seven novel, epistatic models with a Bonferroni corrected p-value of association <; 0.06. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199331","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990754
Shanshan Li, Zengrong Liu, Ruiqi Wang
During central nervous system (CNS) developing, Hes1 shows short period oscillations in progenitor cells, while stable low levels in neurons. The reason why diverse expression modes of Hes1 exist remains unknown. Here, we develop a mathematical model involving Hes1 and BM88, with the aim of understanding the complex molecular mechanism that orchestrates the processes of neural fate decision. Our simple but fundamental model can account for both Hes1 oscillations observed in neural progenitors and Hes1 regulation to BM88 in differentiation progress. Our results suggest that a relatively simple network is capable of accounting for some fundamental principles in progenitor maintenance and differentiation.
{"title":"Neural fate decisions mediated by oscillatory and sustained Hes1","authors":"Shanshan Li, Zengrong Liu, Ruiqi Wang","doi":"10.1109/ISB.2014.6990754","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990754","url":null,"abstract":"During central nervous system (CNS) developing, Hes1 shows short period oscillations in progenitor cells, while stable low levels in neurons. The reason why diverse expression modes of Hes1 exist remains unknown. Here, we develop a mathematical model involving Hes1 and BM88, with the aim of understanding the complex molecular mechanism that orchestrates the processes of neural fate decision. Our simple but fundamental model can account for both Hes1 oscillations observed in neural progenitors and Hes1 regulation to BM88 in differentiation progress. Our results suggest that a relatively simple network is capable of accounting for some fundamental principles in progenitor maintenance and differentiation.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124273115","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990753
B. Qu, A. Gabric, Peijuan Gu, Meifang Zeng
Researches on Arctic aerosol, ice cover and cloud cover have received great attention and it related to the regional even global climate changing. We here study the distributions and the coupling relationships of AOD, cloud cover (CLD) and ice cover (ICE) in the Greenland Sea (20°W-10°E, 70°N-80°N) during 2003-2012. Enhanced statistics methods, such as lag regression method and co-integration analysis method are used for correlation and regression analysis. According to the 10 years satellite data, AOD was high in spring, and low in summer. Generally, AOD was higher down south and lower up north. CLD and AOD mainly had negative correlations and ICE and AOD had positive correlations. According to the lag regression analysis by statistical software EViews, both the peaks of CLD and peaks of ICE were all 1 month earlier than the peak of AOD. The co-integration test suggested that both ICE(-1) and CLD(-1) and AOD were all zero-order integration, and there was no unit root in the residual, so there all had long-run equilibrium relationships. ICE and AOD were stationary series, and the residual had no unit root, they were good coupling. The melting of sea ice and decreasing of cloud cover would all result in the increasing of the AOD content. However, the relationship between AOD and CLD was weaker than the relationship between AOD and ICE, indicating that the aerosol in Arctic mostly came from the sea rather than from the air.
{"title":"The correlation and regression analysis on aerosol optical depth, ice cover and cloud cover in Greenland Sea","authors":"B. Qu, A. Gabric, Peijuan Gu, Meifang Zeng","doi":"10.1109/ISB.2014.6990753","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990753","url":null,"abstract":"Researches on Arctic aerosol, ice cover and cloud cover have received great attention and it related to the regional even global climate changing. We here study the distributions and the coupling relationships of AOD, cloud cover (CLD) and ice cover (ICE) in the Greenland Sea (20°W-10°E, 70°N-80°N) during 2003-2012. Enhanced statistics methods, such as lag regression method and co-integration analysis method are used for correlation and regression analysis. According to the 10 years satellite data, AOD was high in spring, and low in summer. Generally, AOD was higher down south and lower up north. CLD and AOD mainly had negative correlations and ICE and AOD had positive correlations. According to the lag regression analysis by statistical software EViews, both the peaks of CLD and peaks of ICE were all 1 month earlier than the peak of AOD. The co-integration test suggested that both ICE(-1) and CLD(-1) and AOD were all zero-order integration, and there was no unit root in the residual, so there all had long-run equilibrium relationships. ICE and AOD were stationary series, and the residual had no unit root, they were good coupling. The melting of sea ice and decreasing of cloud cover would all result in the increasing of the AOD content. However, the relationship between AOD and CLD was weaker than the relationship between AOD and ICE, indicating that the aerosol in Arctic mostly came from the sea rather than from the air.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114880860","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990743
Shuhao Sun, F. Klebaner, Tianhai Tian
Cancer of the pancreas is a highly lethal disease and has an extremely poor prognosis. It is the fourth leading cause of death from cancer in the US and the twelfth worldwide. There are currently only few therapeutic options for patients with pancreatic cancer. Hence new insights into the pathogenesis of this lethal disease are urgently needed. In recent years, extensive biological research has been conducted to study the mechanisms that control the initiation and progression of pancreas cancer. Mathematical models have also been used to present quantitative analysis and predict reasonable time schemes for the progression of pancreatic cancer. However, in those published articles, it was assumed that the mutation rate was constant, which is not realistic. In this work, we present a new approach using non-constant mutation rate and hence reveal several important biological parameters of cancer progression, such as initial mutation rate as well as doubling time (or selective advantage coefficients) in different stages, and eventually present a better time scheme. Under more realistic assumptions regarding gene mutation and a more reasonable mutation rate, the averaged values of doubling time and selective advantage coefficient generated by our model are consistent with the predictions made by the published models.
{"title":"A new approach for estimating the progression of pancreatic cancer","authors":"Shuhao Sun, F. Klebaner, Tianhai Tian","doi":"10.1109/ISB.2014.6990743","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990743","url":null,"abstract":"Cancer of the pancreas is a highly lethal disease and has an extremely poor prognosis. It is the fourth leading cause of death from cancer in the US and the twelfth worldwide. There are currently only few therapeutic options for patients with pancreatic cancer. Hence new insights into the pathogenesis of this lethal disease are urgently needed. In recent years, extensive biological research has been conducted to study the mechanisms that control the initiation and progression of pancreas cancer. Mathematical models have also been used to present quantitative analysis and predict reasonable time schemes for the progression of pancreatic cancer. However, in those published articles, it was assumed that the mutation rate was constant, which is not realistic. In this work, we present a new approach using non-constant mutation rate and hence reveal several important biological parameters of cancer progression, such as initial mutation rate as well as doubling time (or selective advantage coefficients) in different stages, and eventually present a better time scheme. Under more realistic assumptions regarding gene mutation and a more reasonable mutation rate, the averaged values of doubling time and selective advantage coefficient generated by our model are consistent with the predictions made by the published models.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124660447","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990426
Ludi Jiang, Yusu He, Yanling Zhang
In this study, based on literatures and web databases, 490 hepatotoxic compounds and 598 non-hepatotoxic compounds were selected as a data set for hepatotoxicity discriminative model generation. 1664 molecular descriptors, including physicochemical, charge distribution and geometrical descriptors, were calculated to characterize the molecular structure of liver toxic compounds. The combination of CfsSubsetEval valuation and BestFirst searching was used to choose molecular descriptors for model construction. With the help of support vector machine (SVM), a discriminative model with high accuracy was built. Meanwhile, the accuracy, sensitivity and specificity of this model were all above 80%. Besides, 23 traditional Chinese medicine compounds with hepatotoxicity were regarded as external validation, so as to further verify the model accuracy. Then, the present model was utilized to identify hepatotoxic compounds in Qingkailing injection. The results demonstrated that present study provides a reliable utility for the hepatotoxic compounds prediction in Chinese Medicinal Materials studies.
{"title":"Prediction of hepatotoxicity of traditional Chinese medicine compounds by support vector machine approach","authors":"Ludi Jiang, Yusu He, Yanling Zhang","doi":"10.1109/ISB.2014.6990426","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990426","url":null,"abstract":"In this study, based on literatures and web databases, 490 hepatotoxic compounds and 598 non-hepatotoxic compounds were selected as a data set for hepatotoxicity discriminative model generation. 1664 molecular descriptors, including physicochemical, charge distribution and geometrical descriptors, were calculated to characterize the molecular structure of liver toxic compounds. The combination of CfsSubsetEval valuation and BestFirst searching was used to choose molecular descriptors for model construction. With the help of support vector machine (SVM), a discriminative model with high accuracy was built. Meanwhile, the accuracy, sensitivity and specificity of this model were all above 80%. Besides, 23 traditional Chinese medicine compounds with hepatotoxicity were regarded as external validation, so as to further verify the model accuracy. Then, the present model was utilized to identify hepatotoxic compounds in Qingkailing injection. The results demonstrated that present study provides a reliable utility for the hepatotoxic compounds prediction in Chinese Medicinal Materials studies.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127634873","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}
The conventional non-strand-specific RNA-seq method is widely used for many studies, but it cannot characterize which strand was the transcript originally came from. Strand-specific RNA library construction methods have been developed to overcome this drawback. Here, we compared transcriptomics data from two mainstream RNA enrichment methods (polyA RNAs selection and ribosomal RNAs deletion) by strand-specific RNA sequencing. Using paired-end strategy, we obtained 175 and 149 million high quality reads without ribosomal RNA reads by ribosomal RNAs deletion and poly(A)+ RNAs selection protocol, respectively. From these reads, rmRNA-seq had lower (53.28%) unique mapping rate than the mRNA-seq (73.89%). But, the ribosomal RNAs deletion protocol detected more known non-coding RNAs, particularly lncRNAs, pseudogenes and snoRNAs. Larger proportion (66.7%) of reads mapping to intronic and intergenic regions in ribosomal RNAs deletion method and fewer percentages (33.3%) of reads aligning to exonic regions compared with poly(A)+ RNAs selection method (35.8% and 64.2%). The ribosomal RNAs deletion protocol provides advantages over the poly(A)+ RNAs selection method in sense-antisense pairs detection. In conclusion, the comparison of these two rRNA enrichment methods provides us insight for utility of each protocol. Moreover, we believe that ribosomal RNAs deletion based strand-specific RNA sequencing show us a more comprehensive view of eukaryotic transcriptomes.
{"title":"Comparative analysis of RNA-seq data from polyA RNAs selection and ribosomal RNAs deletion protocol by strand-specific RNA sequencing technology","authors":"Lingjie Fu, Meili Chen, Jiayan Wu, Jingfa Xiao, Zhewen Zhang","doi":"10.1109/ISB.2014.6990734","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990734","url":null,"abstract":"The conventional non-strand-specific RNA-seq method is widely used for many studies, but it cannot characterize which strand was the transcript originally came from. Strand-specific RNA library construction methods have been developed to overcome this drawback. Here, we compared transcriptomics data from two mainstream RNA enrichment methods (polyA RNAs selection and ribosomal RNAs deletion) by strand-specific RNA sequencing. Using paired-end strategy, we obtained 175 and 149 million high quality reads without ribosomal RNA reads by ribosomal RNAs deletion and poly(A)+ RNAs selection protocol, respectively. From these reads, rmRNA-seq had lower (53.28%) unique mapping rate than the mRNA-seq (73.89%). But, the ribosomal RNAs deletion protocol detected more known non-coding RNAs, particularly lncRNAs, pseudogenes and snoRNAs. Larger proportion (66.7%) of reads mapping to intronic and intergenic regions in ribosomal RNAs deletion method and fewer percentages (33.3%) of reads aligning to exonic regions compared with poly(A)+ RNAs selection method (35.8% and 64.2%). The ribosomal RNAs deletion protocol provides advantages over the poly(A)+ RNAs selection method in sense-antisense pairs detection. In conclusion, the comparison of these two rRNA enrichment methods provides us insight for utility of each protocol. Moreover, we believe that ribosomal RNAs deletion based strand-specific RNA sequencing show us a more comprehensive view of eukaryotic transcriptomes.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126286521","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990735
Zhiping Liu
Many critical biological processes are strongly related to protein-RNA interactions. Revealing the structure motifs of performing protein-RNA binding function will provide valuable information for deciphering their interaction mechanisms and benefit complementary structure designs in bioengineering. In this work, we provide a study of systematic identification of protein structure motifs of RNA-binding sites in form of pockets on protein surfaces by clustering these local structure patterns into similar groups. We also identify the crucial recognition patterns and the structural complementary features in the protein-RNA binding events.
{"title":"Systematic identification of local structure binding motifs in protein-RNA recognition","authors":"Zhiping Liu","doi":"10.1109/ISB.2014.6990735","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990735","url":null,"abstract":"Many critical biological processes are strongly related to protein-RNA interactions. Revealing the structure motifs of performing protein-RNA binding function will provide valuable information for deciphering their interaction mechanisms and benefit complementary structure designs in bioengineering. In this work, we provide a study of systematic identification of protein structure motifs of RNA-binding sites in form of pockets on protein surfaces by clustering these local structure patterns into similar groups. We also identify the crucial recognition patterns and the structural complementary features in the protein-RNA binding events.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"49 20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122213604","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 : 2014-12-18DOI: 10.1109/ISB.2014.6990422
Yiru Zhang, Chang-Chang Cao, Hongde Liu, Xiao Sun
Nucleosomes are the basic units of eukaryotic chromatin. The nucleosome positioning is dynamic for various cell types and biological states, resulting in specific gene regulation. Currently, there is no approach to find the correspondence between two sets of nucleosomes to reveal the difference of their positions. We develop a method for nucleosome positions alignment based on the dynamic programming algorithm, which can quantify the changes in nucleosome locations with scores and evaluate regional dynamics changes including translation and missing. Given the result of a peak list stands for nucleosome positions, to align the peaks from two samples, our method accumulate all pair scores for match, replacement or deletion and choose the maximum one as the optimal alignment. From nucleosome alignment we can find one-by-one correspondence between nucleosome positions in different cell stages and the conservative stable and variable regions, which can be used to recognize dynamic behaviors of nucleosome shift and eviction.
{"title":"A dynamic programming algorithm for nucleosome positions alignment","authors":"Yiru Zhang, Chang-Chang Cao, Hongde Liu, Xiao Sun","doi":"10.1109/ISB.2014.6990422","DOIUrl":"https://doi.org/10.1109/ISB.2014.6990422","url":null,"abstract":"Nucleosomes are the basic units of eukaryotic chromatin. The nucleosome positioning is dynamic for various cell types and biological states, resulting in specific gene regulation. Currently, there is no approach to find the correspondence between two sets of nucleosomes to reveal the difference of their positions. We develop a method for nucleosome positions alignment based on the dynamic programming algorithm, which can quantify the changes in nucleosome locations with scores and evaluate regional dynamics changes including translation and missing. Given the result of a peak list stands for nucleosome positions, to align the peaks from two samples, our method accumulate all pair scores for match, replacement or deletion and choose the maximum one as the optimal alignment. From nucleosome alignment we can find one-by-one correspondence between nucleosome positions in different cell stages and the conservative stable and variable regions, which can be used to recognize dynamic behaviors of nucleosome shift and eviction.","PeriodicalId":249103,"journal":{"name":"2014 8th International Conference on Systems Biology (ISB)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133452991","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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