2013 7th International Conference on Systems Biology (ISB)最新文献

A method for discriminating native protein-DNA complexes from decoys using spatial specific scoring matrices 一种利用空间特异性评分矩阵区分天然蛋白质- dna复合物和诱饵的方法

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623804

Wen Cheng, Changhui Yan

{"title":"A method for discriminating native protein-DNA complexes from decoys using spatial specific scoring matrices","authors":"Wen Cheng, Changhui Yan","doi":"10.1109/ISB.2013.6623804","DOIUrl":"https://doi.org/10.1109/ISB.2013.6623804","url":null,"abstract":"Decoding protein-DNA interactions is important to understanding gene regulation and has been investigated by worldwide scientists for a long time. However, many aspects of the interactions still need to be uncovered. The crystal structures of protein-DNA complexes reveal detailed atomic interactions between the proteins and DNA and are an excellent resource for investigating the interactions. In this study, we profiled the spatial distribution of protein atoms around six structural components of the DNA, which are the four bases, the deoxyribose sugar and the phosphate group. The resultant profiles not only revealed the preferred atomic interactions across the protein-DNA interface but also captured the spatial orientation of the interactions. The profiles are a useful tool for investigating protein-DNA interactions. We tested the strength of profiles in two experiments, discrimination of native protein-DNA complexes from decoys with mutant DNA and discrimination of native protein-DNA complexes from near-native docking decoys. The profiles achieved an average Z-score of 7.41 and 3.22 respective on benchmark datasets for the tests, both are better than other knowledge-based energy functions that model protein-DNA interaction based on atom pairs.","PeriodicalId":151775,"journal":{"name":"2013 7th International Conference on Systems Biology (ISB)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127674534","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}

引用次数: 0

Subcellular localization prediction of apoptosis proteins based on the data mining for amino acid index database 基于氨基酸索引数据库数据挖掘的凋亡蛋白亚细胞定位预测

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623792

Zhuoxing Shi, Qi Dai, P. He, Yu-Hua Yao, Bo Liao

引用次数: 1

GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU GPU- meta - storms:使用GPU计算大量微生物群落之间的相似性

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623796

Xiaoquan Su, Xuetao Wang, Jian Xu, K. Ning

{"title":"GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU","authors":"Xiaoquan Su, Xuetao Wang, Jian Xu, K. Ning","doi":"10.1109/ISB.2013.6623796","DOIUrl":"https://doi.org/10.1109/ISB.2013.6623796","url":null,"abstract":"With the development of next-generation sequencing and metagenomic technologies, the number of metagenomic samples of microbial communities is increasing with exponential speed. The comparison among metagenomic samples could facilitate the data mining of the valuable yet hidden biological information held in the massive metagenomic data. However, current methods for metagenomic comparison are limited by their ability to process very large number of samples each with large data size. In this work, we have developed an optimized GPU-based metagenomic comparison algorithm, GPU-Meta-Storms, to evaluate the quantitative phylogenetic similarity among massive metagenomic samples, and implemented it using CUDA (Compute Unified Device Architecture) and C++ programming. The GPU-Meta-Storms program is optimized for CUDA with non-recursive transform, register recycle, memory alignment and so on. Our results have shown that with the optimization of the phylogenetic comparison algorithm, memory accessing strategy and parallelization mechanism on many-core hardware architecture, GPU-Meta-Storms could compute the pair-wise similarity matrix for 1920 metagenomic samples in 4 minutes, which gained a speed-up of more than 1000 times compared to CPU version Meta-Storms on single-core CPU, and more than 100 times on 16-core CPU. Therefore, the high-performance of GPU-Meta-Storms in comparison with massive metagenomic samples could thus enable in-depth data mining from massive metagenomic data, and make the real-time analysis and monitoring of constantly-changing metagenomic samples possible.","PeriodicalId":151775,"journal":{"name":"2013 7th International Conference on Systems Biology (ISB)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630629","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}

引用次数: 1

A stochastic simulation algorithm for biochemical reactions with delays 具有时滞的生化反应随机模拟算法

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623803

Pei Wang, Jinhu Lu, Li-di Wan, Yao Chen

{"title":"A stochastic simulation algorithm for biochemical reactions with delays","authors":"Pei Wang, Jinhu Lu, Li-di Wan, Yao Chen","doi":"10.1109/ISB.2013.6623803","DOIUrl":"https://doi.org/10.1109/ISB.2013.6623803","url":null,"abstract":"Biochemical systems can be described by biochemical reactions. Biochemical reactions can be investigated through mathematical modeling and stochastic simulations. Deterministic and stochastic models are two basic categories of models for biochemical reactions. Due to transmembrane transportation of biochemical species and delayed degradation, time delays are ubiquitous in coupled biochemical systems. Therefore, models for biochemical reactions can be further classified into delayed and un-delayed ones. For biochemical systems without delays, researchers have established the connections between deterministic models and stochastic models directly from the deterministic ones. For delayed biochemical systems, researchers have proposed some stochastic simulation methods to cope with biochemical reactions with time delays. However, the existing delayed stochastic simulation algorithms (SSA) are all incapable of realizing the comparison between highly nonlinear deterministic delayed models and stochastic models directly from the the deterministic ones. In this paper, we proposed a delayed SSA, which can realize the comparison between deterministic models and its stochastic counterparts. Furthermore, one can also use the algorithm to investigate intrinsic noise-induced behaviors, and the effect of system volumes. Several numerical examples show the effectiveness and correctness of our algorithm.","PeriodicalId":151775,"journal":{"name":"2013 7th International Conference on Systems Biology (ISB)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133976426","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}

引用次数: 8

Meta-analysis on gene regulatory networks discovered by pairwise Granger causality 双格兰杰因果关系发现的基因调控网络meta分析

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623806

G. Tam, Y. Hung, Chunqi Chang

引用次数: 9

Prediction of enzyme catalytic sites on protein using a graph kernel method 用图核法预测蛋白质上酶催化位点

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623789

Benaragama V. M. V. Sanjaka, Changhui Yan

{"title":"Prediction of enzyme catalytic sites on protein using a graph kernel method","authors":"Benaragama V. M. V. Sanjaka, Changhui Yan","doi":"10.1109/ISB.2013.6623789","DOIUrl":"https://doi.org/10.1109/ISB.2013.6623789","url":null,"abstract":"Structural Genomics projects are producing structural data for proteins at an unprecedented speed. The functions of many of these protein structures are still unknown. To decipher the functions of these proteins and identify functional sites on their structures have become an urgent task. In this study, we developed an innovative graph method to represent protein surface based on how amino acid residues contact with each other. Then, we implemented a shortest-path graph kernel method to measure the similarities between graphs. We tried three variants of the nearest neighbor method to predict enzyme catalytic sites using the similarity measurement given by the shortest-path graph kernel. The prediction methods were evaluated using the leave-one-out cross validation. The methods achieved accuracy as high as 77.1%. We sorted all examples in the order of decreasing prediction scores. The results revealed that the positive examples (catalytic site residues) were associated with higher prediction scores and they were enriched in the region of top 10 percentile. Our results showed that the proposed methods were able to capture the structural similarity between enzyme catalytic sites and would provide a useful tool for catalytic site prediction.","PeriodicalId":151775,"journal":{"name":"2013 7th International Conference on Systems Biology (ISB)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115995018","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}

引用次数: 2

Exploring the interaction patterns in seasonal marine microbial communities with network analysis 利用网络分析探讨季节性海洋微生物群落的相互作用模式

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623795

Shaowu Zhang, Ze-Gang Wei, Chen Zhou, Yu-Chen Zhang, Tinghe Zhang

{"title":"Exploring the interaction patterns in seasonal marine microbial communities with network analysis","authors":"Shaowu Zhang, Ze-Gang Wei, Chen Zhou, Yu-Chen Zhang, Tinghe Zhang","doi":"10.1109/ISB.2013.6623795","DOIUrl":"https://doi.org/10.1109/ISB.2013.6623795","url":null,"abstract":"With the development of high-throughput and lowcost sequencing technology, a large amount of marine microbial sequences is generated. So, it is possible to research more uncultivated marine microbes. The interaction patterns of marine microbial species and marine microbial diversity are hidden in these large amount sequences. Understanding the interaction pattern and structure of marine microbe have a high potential for exploiting the marine resources. Yet, very few marine microbial interaction patterns are well characterized even with the weight of research effort presently devoted to this field. In this paper, based on the 16S rRNA tag pyrosequencing data taken monthly over 6 years at a temperate marine coastal sits in West English Channel, we employed the CROP unsupervised probabilistic Bayesian clustering algorithm to generate the operational taxonomic units (OTUs), and utilized the PCA-CMI algorithm to construct the spring, summer, fall, and winter seasonal marine microbial interaction networks. From the four seasonal microbial networks, we introduced a novel module detecting algorithm called as DIDE, by integrating the dense subgraph, edge clustering coefficient and local modularity, to detect the interaction pattern of marine microbe in four seasons. The analysis of network topological parameters shows that the four seasonal marine microbial interaction networks have characters of complex networks, and the topological structure difference among the four networks maybe caused by the seasonal environmental factors. The marine microbial interaction patterns detected by DIDE algorithm in four seasons show evidence of seasonally interaction pattern diversity. The interaction pattern diversity of fall and winter is more than that of spring and fall, which indicates that the seasonal variability might have the greatest influence on the marine microbe diversity.","PeriodicalId":151775,"journal":{"name":"2013 7th International Conference on Systems Biology (ISB)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122689992","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}

引用次数: 4

Predicting the non-compact conformation of amino acid sequence by particle swarm optimization 用粒子群算法预测氨基酸序列的非紧致构象

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623805

Yuzhen Guo, Yong Wang

引用次数: 1

Colored Petri nets for multiscale systems biology - Current modeling and analysis capabilities in snoopy 用于多尺度系统生物学的彩色Petri网。snoopy中当前的建模和分析能力

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623788

Fei Liu, M. Heiner, Ming-Jang Yang

引用次数: 4

Detect taxonomy-specific pathway associations with environmental factors using metagenomic data 使用宏基因组数据检测与环境因素相关的分类特异性途径

2013 7th International Conference on Systems Biology (ISB) Pub Date : 2013-10-10 DOI: 10.1109/ISB.2013.6623809

Xue Tian, Fuzhou Gong, Shi-Hua Zhang

引用次数: 1