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Int. J. Knowl. Discov. Bioinform.最新文献

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Combinatorial Optimization Algorithms for Metabolic Networks Alignments and Their Applications 代谢网络比对的组合优化算法及其应用
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/jkdb.2011010101
Qiong Cheng, A. Zelikovsky
{"title":"Combinatorial Optimization Algorithms for Metabolic Networks Alignments and Their Applications","authors":"Qiong Cheng, A. Zelikovsky","doi":"10.4018/jkdb.2011010101","DOIUrl":"https://doi.org/10.4018/jkdb.2011010101","url":null,"abstract":"The accumulation of high-throughput genomic and proteomic data allows for reconstruction of large and complex metabolic networks. To analyze accumulated data and reconstructed networks, it is critical to identify network patterns and evolutionary relations between metabolic networks; finding similar networks is computationally challenging. Based on gene duplication and function sharing in biological networks, a network alignment problem is formulated that asks the optimal vertex-to-vertex mapping allowing path contraction, different types of vertex deletion, and vertex insertions. This paper presents fixed parameter tractable combinatorial optimization algorithms, which take into account the similarity of both the enzymes’ functions arbitrary network topologies. Results are evaluated by the randomized P-Value computation. The authors perform pairwise alignments of all pathways for four organisms and find a set of statistically significant pathway similarities. The network alignment is used to identify pathway holes that are the result of inconsistencies and missing enzymes. The authors propose a framework of filling pathway holes by including database searches for missing enzymes and proteins with the matching prosites and further finding potential candidates with high sequence similarity.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"347 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130230239","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
GEView (Gene Expression View) Tool for Intuitive and High Accessible Visualization of Expression Data for Non-Programmer Biologists GEView(基因表达视图)工具，为非程序员生物学家提供直观和高度可访问的表达数据可视化
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/IJKDB.2018010107
Libi Hertzberg, Assif Yitzhaky, M. Pasmanik-Chor
{"title":"GEView (Gene Expression View) Tool for Intuitive and High Accessible Visualization of Expression Data for Non-Programmer Biologists","authors":"Libi Hertzberg, Assif Yitzhaky, M. Pasmanik-Chor","doi":"10.4018/IJKDB.2018010107","DOIUrl":"https://doi.org/10.4018/IJKDB.2018010107","url":null,"abstract":"This article describes how the last decade has been characterized by the production of huge amounts of different types of biological data. Following that, a flood of bioinformatics tools have been published. However, many of these tools are commercial, or require computational skills. In addition, not all tools provide intuitive and highly accessible visualization of the results. The authors have developed GEView (Gene Expression View), which is a free, user-friendly tool harboring several existing algorithms and statistical methods for the analysis of high-throughput gene, microRNA or protein expression data. It can be used to perform basic analysis such as quality control, outlier detection, batch correction and differential expression analysis, through a single intuitive graphical user interface. GEView is unique in its simplicity and highly accessible visualization it provides. Together with its basic and intuitive functionality it allows Bio-Medical scientists with no computational skills to independently analyze and visualize high-throughput data produced in their own labs.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121801421","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
Finding Minimum Reaction Cuts of Metabolic Networks Under a Boolean Model Using Integer Programming and Feedback Vertex Sets 利用整数规划和反馈顶点集求布尔模型下代谢网络的最小反应切
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/jkdb.2010100202
Takeyuki Tamura, Kazuhiro Takemoto, T. Akutsu
{"title":"Finding Minimum Reaction Cuts of Metabolic Networks Under a Boolean Model Using Integer Programming and Feedback Vertex Sets","authors":"Takeyuki Tamura, Kazuhiro Takemoto, T. Akutsu","doi":"10.4018/jkdb.2010100202","DOIUrl":"https://doi.org/10.4018/jkdb.2010100202","url":null,"abstract":"In this paper, the authors consider the problem of, given a metabolic network, a set of source compounds and a set of target compounds, finding a minimum size reaction cut, where a Boolean model is used as a model of metabolic networks. The problem has potential applications to measurement of structural robustness of metabolic networks and detection of drug targets. They develop an integer programming-based method for this optimization problem. In order to cope with cycles and reversible reactions, they further develop a novel integer programming (IP) formalization method using a feedback vertex set (FVS). When applied to an E. coli metabolic network consisting of Glycolysis/Glyconeogenesis, Citrate cycle and Pentose phosphate pathway obtained from KEGG database, the FVS-based method can find an optimal set of reactions to be inactivated much faster than a naive IP-based method and several times faster than a flux balance-based method. The authors also confirm that our proposed method works even for large networks and discuss the biological meaning of our results.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124226881","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: 52
Transcriptome-To-Metabolome™ Biosimulation Reveals Human Hippocampal Hypometabolism with Age and Alzheimer's Disease 转录组-代谢组™生物模拟揭示人类海马代谢降低与年龄和阿尔茨海默病
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/ijkdb.2011040101
C. Phelix, R. LeBaron, D. Roberson, R. Villanueva, G. Villareal, Omid B. Rahimi, S. Siedlak, Xiongwei Zhu, George Perry
{"title":"Transcriptome-To-Metabolome™ Biosimulation Reveals Human Hippocampal Hypometabolism with Age and Alzheimer's Disease","authors":"C. Phelix, R. LeBaron, D. Roberson, R. Villanueva, G. Villareal, Omid B. Rahimi, S. Siedlak, Xiongwei Zhu, George Perry","doi":"10.4018/ijkdb.2011040101","DOIUrl":"https://doi.org/10.4018/ijkdb.2011040101","url":null,"abstract":"","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123097752","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: 3
Local Optima Avoidance in GA Biclustering using Map Reduce 基于Map约简的GA双聚类局部最优避免
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/IJKDB.2016010104
R. Gowri, R. Rathipriya
{"title":"Local Optima Avoidance in GA Biclustering using Map Reduce","authors":"R. Gowri, R. Rathipriya","doi":"10.4018/IJKDB.2016010104","DOIUrl":"https://doi.org/10.4018/IJKDB.2016010104","url":null,"abstract":"One of the prominent issues in Genetic Algorithm GA is premature convergence on local optima. This restricts the enhanced optimal solution searching in the entire search space. Population size is one of the influencing factors in Genetic Algorithm. Increasing the population size will improvise the randomized searching and maintains the diversity in the population. It also increases its computational complexity. Especially in GA Biclustering GABiC, the search should be randomized to find more optimal patterns. In this paper, a novel approach for population setup in MapReduce framework is proposed. The maximal population is split into population sets, and these groups will proceed searching in parallel using MapReduce framework. This approach is attempted for biclustering the gene expression dataset in this paper. The performance of this proposed work seems promising on comparing its results with those obtained from previous hybridized optimization approaches. This approach will also handle data scalability issues and applicable to the big data biclustering problems.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122653762","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
Medical Domain Knowledge and Associative Classification Rules in Diagnosis 医学领域知识与诊断中的关联分类规则
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/jkdb.2011010104
Sung-ho Ha
{"title":"Medical Domain Knowledge and Associative Classification Rules in Diagnosis","authors":"Sung-ho Ha","doi":"10.4018/jkdb.2011010104","DOIUrl":"https://doi.org/10.4018/jkdb.2011010104","url":null,"abstract":"Hospital information systems have been frustrated by problems that include congestion, long wait time, and delayed patient care over decades. To solve these problems, data mining techniques have been used in medical research for many years and are known to be effective. Therefore, this study examines building a hybrid data mining methodology, combining medical domain knowledge and associative classification rules. Real world emergency data are collected from a hospital and the methodology is evaluated by comparing it with other techniques. The methodology is expected to help physicians to make rapid and accurate diagnosis of chest diseases.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129557121","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: 9
Detection of Breast Cancer by the Identification of Circulating Tumor Cells Using Association Rule Mining 基于关联规则挖掘的循环肿瘤细胞识别检测乳腺癌
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/IJKDB.2016010102
S. Jananee, R. Nedunchelian
{"title":"Detection of Breast Cancer by the Identification of Circulating Tumor Cells Using Association Rule Mining","authors":"S. Jananee, R. Nedunchelian","doi":"10.4018/IJKDB.2016010102","DOIUrl":"https://doi.org/10.4018/IJKDB.2016010102","url":null,"abstract":"Circulating Tumor Cells CTCs are cells that have shed into the vasculate from the primary tumor and circulate into the blood stream. In this proposed work, the major genes causing the breast cancer is identified by the principle of Association Rule. The trained set and training set is made to upload on the data store. By associating each row of a training set to all the rows of the trained data is done and the report is generated. The Baum welch process is called for the estimation of actual probabilities and emission probabilities by calculating its log likelihood factor which gives the high Priority gene values that are responsible for the cause of cancer. Based on this cell category is splitted into three clusters such as carcinoma level, metastasis level and Kaposi sarcoma. On each cluster it finds the highest priority value in it and classifies into high, low and medium values. On extraction of these higher gene values yields the major responsible genes causing breast cancer. Finally, the obtained results are validated through hierarchical clustering.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127808459","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
Estimation of Fractal Dimension in Different Color Model 不同颜色模型的分形维数估计
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/IJKDB.2018010106
S. Kisan, Sarojananda Mishra, Ajay Chawda, Sanjay Nayak
{"title":"Estimation of Fractal Dimension in Different Color Model","authors":"S. Kisan, Sarojananda Mishra, Ajay Chawda, Sanjay Nayak","doi":"10.4018/IJKDB.2018010106","DOIUrl":"https://doi.org/10.4018/IJKDB.2018010106","url":null,"abstract":"Thisarticledescribeshowthetermfractaldimension(FD)playsavitalroleinfractalgeometry.It isadegreethatdistinguishesthecomplexityandtheirregularityoffractals,denotingtheamountof spacefilledup.Therearemanyprocedurestoevaluatethedimensionforfractalsurfaces,likebox count,differentialboxcount,andtheimproveddifferentialboxcountmethod.Thesemethodsare basicallyusedforgreyscaleimages.Theauthors’objectiveinthisarticleistoestimatethefractal dimensionofcolorimagesusingdifferentcolormodels.Theauthorshaveproposedanovelmethod fortheestimationinCMYandHSVcolorspaces.Inordertoachievetheresult,theyperformedtest operationbytakingnumberofcolorimagesinRGBcolorspace.Theauthorshavepresentedtheir experimentalresultsanddiscussedtheissuesthatcharacterizetheapproach.Attheend,theauthors haveconcludedthearticlewiththeanalysisofcalculatedFDsforimageswithdifferentcolorspace. KEywoRDS Box Count, CMY, DBC, Fractal Dimension, Fractal Geometry, HSV, Improved DBC, RGB","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122365256","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
Property and Personality Rights with Regard to Biobanks: A Layered System with Germany as an Example 生物银行的产权与人格权:以德国为例的分层制度
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/ijkdb.2014010102
Jürgen Robienski, J. Simon
{"title":"Property and Personality Rights with Regard to Biobanks: A Layered System with Germany as an Example","authors":"Jürgen Robienski, J. Simon","doi":"10.4018/ijkdb.2014010102","DOIUrl":"https://doi.org/10.4018/ijkdb.2014010102","url":null,"abstract":"In the field of genetic research and the subsequent rise of biobanks an intensive discussion is taking place on national and international levels about property and personality rights to one's own body and body parts. The authors attempt to develop on the basis of the current controversially discussed law a concept of property, which can solve the legal and bioethical problems of the multiple use of human samples. Therefore, the question will be discussed whether a person is eligible to claim property rights to the tissue, which was separated from him. The authors' opinion is that this person only looses his property rights when all data are completely anonymised. Also the trustee model could be an efficient model, in which the tissue is safeguarded and pseudonymised by a trustee, to preserve the interests of the former owner of the human samples, but concurrently support the interests of the users.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132043494","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
Biological and Medical Big Data Mining 生物和医学大数据挖掘
Int. J. Knowl. Discov. Bioinform. Pub Date : 1900-01-01 DOI: 10.4018/ijkdb.2014010104
G. Tzanis
{"title":"Biological and Medical Big Data Mining","authors":"G. Tzanis","doi":"10.4018/ijkdb.2014010104","DOIUrl":"https://doi.org/10.4018/ijkdb.2014010104","url":null,"abstract":"This paper discusses the concept of big data mining in the domain of biology and medicine. Biological and medical data are increasing at very rapid rates, which in many cases outpace even Moore's law. This is the result of recent technological development, as well as the exploratory attitude of human beings, that prompts scientists to answer more questions by conducting more experiments. Representative examples are the advances in sequencing and medical imaging technologies. Challenges posed by this data deluge, and the emerging opportunities of their efficient management and analysis are also part of the discussion. The major emphasis is given to the most common biological and medical data mining applications.","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123812735","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: 21
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