Pub Date : 2010-12-01DOI: 10.1109/BIBMW.2010.5703932
Ting Li, H. Bonkovsky, Jun-tao Guo
Heme is an essential molecule and plays vital roles in many biological processes. The structural determination of a large number of heme proteins has made it possible to study the detailed chemical and structural properties of heme binding environment. Knowledge of these characteristics can provide valuable guidelines in the design of novel heme proteins and help us predict unknown heme binding proteins. In this paper, we constructed a non-redundant dataset of 125 heme-binding protein chains and found that these heme proteins encompass at least 31 different structural folds. Heme binding pockets are enriched in aromatics and non-polar amino acids with fewer charged residues. The differences between apo and holo forms of heme proteins in terms of the structure and the binding pockets have been investigated. In most cases the proteins undergo small conformational changes upon heme binding.
{"title":"Structural analysis of heme proteins: Implication for design and prediction","authors":"Ting Li, H. Bonkovsky, Jun-tao Guo","doi":"10.1109/BIBMW.2010.5703932","DOIUrl":"https://doi.org/10.1109/BIBMW.2010.5703932","url":null,"abstract":"Heme is an essential molecule and plays vital roles in many biological processes. The structural determination of a large number of heme proteins has made it possible to study the detailed chemical and structural properties of heme binding environment. Knowledge of these characteristics can provide valuable guidelines in the design of novel heme proteins and help us predict unknown heme binding proteins. In this paper, we constructed a non-redundant dataset of 125 heme-binding protein chains and found that these heme proteins encompass at least 31 different structural folds. Heme binding pockets are enriched in aromatics and non-polar amino acids with fewer charged residues. The differences between apo and holo forms of heme proteins in terms of the structure and the binding pockets have been investigated. In most cases the proteins undergo small conformational changes upon heme binding.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125437727","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 : 2010-12-01DOI: 10.1109/BIBMW.2010.5703805
B. Zineddin, Zidong Wang, Xiaohui Liu
Despite the latest improvements in the microarray technology, many developments are needed particularly in the image processing stage. Some hardware implementations of microarray image processing have been proposed and proved to be a promising alternative to the currently available software systems. However, the main drawback is the unsuitable addressing of the quantification of the gene spots which depend on many assumptions. It is our aim in this paper to present a new Image Reconstruction algorithm using Cellular Neural Network, which solves the Navier-Stokes equation. This algorithm offers a robust method to estimate the background signal within the gene spot region. Quantitative comparisons are carried out, between our approach and some available methods in terms of objective standpoint. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner, and also, in a remarkably efficient time.
{"title":"Cellular Neural Networks, Navier-Stokes equation and microarray image reconstruction","authors":"B. Zineddin, Zidong Wang, Xiaohui Liu","doi":"10.1109/BIBMW.2010.5703805","DOIUrl":"https://doi.org/10.1109/BIBMW.2010.5703805","url":null,"abstract":"Despite the latest improvements in the microarray technology, many developments are needed particularly in the image processing stage. Some hardware implementations of microarray image processing have been proposed and proved to be a promising alternative to the currently available software systems. However, the main drawback is the unsuitable addressing of the quantification of the gene spots which depend on many assumptions. It is our aim in this paper to present a new Image Reconstruction algorithm using Cellular Neural Network, which solves the Navier-Stokes equation. This algorithm offers a robust method to estimate the background signal within the gene spot region. Quantitative comparisons are carried out, between our approach and some available methods in terms of objective standpoint. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner, and also, in a remarkably efficient time.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114050112","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 : 1900-01-01DOI: 10.1109/BIBMW.2011.6112479
Heng Weng, Chuanliang Yi, Yingzi Lin, Y. Zeng, Yang Li, S. Wu, Dacan Chen, Hao Fu
Purpose: To develop an intelligent analysis system applying in Traditional Chinese Medicine (TCM) medical records, according to the language description characteristics of TCM; Methodology: Constructing semantic analysis system by several relevant technique, such as corpus database training, Chinese word segmentation and latent semantic analysis modeling etc, through the study of the language characteristics of medical records and the demands in research of TCM; Findings: A corpus database for specialties has been established by processing over 50,000 medical records of TCM; Over 1,400 records regarding to kidney disease have been evaluated automatically by their symptoms descriptions; The result shows a high consistency compared with the human analysis of random sample; Conclusion: It displays the feasibility and advantage of the whole system designing for unstructured medical records, and provides data mining method for massive unstructured data of TCM in integrated solution.
{"title":"Construction of semantic analysis system for Traditional Chinese Medicine unstructured medical records","authors":"Heng Weng, Chuanliang Yi, Yingzi Lin, Y. Zeng, Yang Li, S. Wu, Dacan Chen, Hao Fu","doi":"10.1109/BIBMW.2011.6112479","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112479","url":null,"abstract":"Purpose: To develop an intelligent analysis system applying in Traditional Chinese Medicine (TCM) medical records, according to the language description characteristics of TCM; Methodology: Constructing semantic analysis system by several relevant technique, such as corpus database training, Chinese word segmentation and latent semantic analysis modeling etc, through the study of the language characteristics of medical records and the demands in research of TCM; Findings: A corpus database for specialties has been established by processing over 50,000 medical records of TCM; Over 1,400 records regarding to kidney disease have been evaluated automatically by their symptoms descriptions; The result shows a high consistency compared with the human analysis of random sample; Conclusion: It displays the feasibility and advantage of the whole system designing for unstructured medical records, and provides data mining method for massive unstructured data of TCM in integrated solution.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","volume":"67 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":"124726399","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 : 1900-01-01DOI: 10.1109/BIBMW.2010.5703898
Guangqin Hu, Xiao-zuo Lu, Bing-hua Zhou, Yufu Luo, Yang-dong Lu, Min Zhu, Xiaoming Liu
Objective: Study the correlation between some parts of Traditional Chinese Medicine (TCM)'s physical examination elements and the parameters of the renal function. Method: Select 935 samples of TCM four diagnostic and syndrome differentiation information from young healthy examinees, study the correlation between these information. Results: there is extremely significant positive correlation coefficient (P<0.01) between the renal function urea nitrogen and those symptoms. It included dry nose, lassitude and heaviness of the limb, loose feces, aphthous stomatitis, dry skin etc. There is significant positive correlation (PP<0.05) between the creatinine etc. There is extremely significant positive correlation (PP<0.01) between the Creatinine and those symptoms including red tongue and bitter taste. Conclusion: Observing the changing of the TCM syndromes and the tongue manifestations, it can improve the accuracy of the physical examination and the syndrome differentiation.
{"title":"Study about the feature of some parts of the Traditional Chinese Medicine(TCM) physical examination correlate with the indexes of the renal function","authors":"Guangqin Hu, Xiao-zuo Lu, Bing-hua Zhou, Yufu Luo, Yang-dong Lu, Min Zhu, Xiaoming Liu","doi":"10.1109/BIBMW.2010.5703898","DOIUrl":"https://doi.org/10.1109/BIBMW.2010.5703898","url":null,"abstract":"Objective: Study the correlation between some parts of Traditional Chinese Medicine (TCM)'s physical examination elements and the parameters of the renal function. Method: Select 935 samples of TCM four diagnostic and syndrome differentiation information from young healthy examinees, study the correlation between these information. Results: there is extremely significant positive correlation coefficient (P<0.01) between the renal function urea nitrogen and those symptoms. It included dry nose, lassitude and heaviness of the limb, loose feces, aphthous stomatitis, dry skin etc. There is significant positive correlation (PP<0.05) between the creatinine etc. There is extremely significant positive correlation (PP<0.01) between the Creatinine and those symptoms including red tongue and bitter taste. Conclusion: Observing the changing of the TCM syndromes and the tongue manifestations, it can improve the accuracy of the physical examination and the syndrome differentiation.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","volume":"36 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":"122870532","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 : 1900-01-01DOI: 10.1109/BIBMW.2012.6470199
L. Mesa, Fernando Niño, L. Kleine
In this work, a methodology for constructing and analysing gene clusters based on gene expression data is proposed. This approach uses data mining algorithms and machine learning methods to discover relationships between genes associated to biological knowledge and regulatory activities for expression experiments conducted under particular conditions of interest. Such gene groups were constructed based on a similarity matrix defined from nonlinear relationships given by a constructed kernel on each data type. Once groups were formed, representative transcription factor binding sites were searched in each cluster in order to categorize them and to find patterns and relationships between genes and transcription factor binding sites. Accordingly, interesting transcription factor binding sites related to gene expression experimental conditions were detected. This confirmed common gene regulation of known binding sites.
{"title":"Identification and analysis of gene clusters in biological data","authors":"L. Mesa, Fernando Niño, L. Kleine","doi":"10.1109/BIBMW.2012.6470199","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470199","url":null,"abstract":"In this work, a methodology for constructing and analysing gene clusters based on gene expression data is proposed. This approach uses data mining algorithms and machine learning methods to discover relationships between genes associated to biological knowledge and regulatory activities for expression experiments conducted under particular conditions of interest. Such gene groups were constructed based on a similarity matrix defined from nonlinear relationships given by a constructed kernel on each data type. Once groups were formed, representative transcription factor binding sites were searched in each cluster in order to categorize them and to find patterns and relationships between genes and transcription factor binding sites. Accordingly, interesting transcription factor binding sites related to gene expression experimental conditions were detected. This confirmed common gene regulation of known binding sites.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","volume":"63 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":"127537040","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 : 1900-01-01DOI: 10.1109/BIBMW.2012.6470319
Nanyue Wang, Dawei Huang, Yanping Chen, Youhua Yu, Zengyu Shan, L. Xue, Bohua Jiang, Tongda Li, Yan Chen, Ying Huang
Objective: To build a viable method to analyze the Pulse-diagnosis signals by the combination of unsupervised learning and supervised learning. Methods: After collecting the pulse waves of patients with chronic obstructive pulmonary disease (COPD) and healthy volunteers, we do pretreatment, parameter extracting basing on harmonic fitting, modeling, and identification by unsupervised learning Principal Component Analysis (PCA) and supervised learning Least-squares Regression (LS) and Least Absolute Shrinkage and Selection Operator (Lasso) with cross-validation step by step for analysis. Result: There is significant difference between COPD patients' pulse waves and the healthy volunteers, and the identification accuracy is about 80%. Features at 3 specific places in radial artery called "youcun" "youguan" "zuochi" in pulse-diagnosis of Traditional Chinese Medicine (TCM) we exacted from the 193 parameters by the 3 methods are especially significant compare with others, and C2youguan is the common one. Conclusion: The method we built basing on the combination of unsupervised learning PCA and supervised learning LS and Lasso is feasible in analyzing the Pulse-diagnosis signals. Furthermore, according to the result of cross-reference by 3 methods and the equation established by Lasso, we can achieve a reliable result by signals of pulse-diagnosis in TCM to identify the healthy volunteers and the patients with COPD. This study might offer some confidence for the realization of computer-aided diagnosis by pulse-diagnosis in TCM, and some important evidence for the scientific of pulse-diagnosis in TCM clinical diagnosis.
{"title":"Signals analysis of pulse-diagnosis in TCM by the combination of unsupervised learning and supervised learning","authors":"Nanyue Wang, Dawei Huang, Yanping Chen, Youhua Yu, Zengyu Shan, L. Xue, Bohua Jiang, Tongda Li, Yan Chen, Ying Huang","doi":"10.1109/BIBMW.2012.6470319","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470319","url":null,"abstract":"Objective: To build a viable method to analyze the Pulse-diagnosis signals by the combination of unsupervised learning and supervised learning. Methods: After collecting the pulse waves of patients with chronic obstructive pulmonary disease (COPD) and healthy volunteers, we do pretreatment, parameter extracting basing on harmonic fitting, modeling, and identification by unsupervised learning Principal Component Analysis (PCA) and supervised learning Least-squares Regression (LS) and Least Absolute Shrinkage and Selection Operator (Lasso) with cross-validation step by step for analysis. Result: There is significant difference between COPD patients' pulse waves and the healthy volunteers, and the identification accuracy is about 80%. Features at 3 specific places in radial artery called \"youcun\" \"youguan\" \"zuochi\" in pulse-diagnosis of Traditional Chinese Medicine (TCM) we exacted from the 193 parameters by the 3 methods are especially significant compare with others, and C2youguan is the common one. Conclusion: The method we built basing on the combination of unsupervised learning PCA and supervised learning LS and Lasso is feasible in analyzing the Pulse-diagnosis signals. Furthermore, according to the result of cross-reference by 3 methods and the equation established by Lasso, we can achieve a reliable result by signals of pulse-diagnosis in TCM to identify the healthy volunteers and the patients with COPD. This study might offer some confidence for the realization of computer-aided diagnosis by pulse-diagnosis in TCM, and some important evidence for the scientific of pulse-diagnosis in TCM clinical diagnosis.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","volume":"1 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":"116777888","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 : 1900-01-01DOI: 10.1109/BIBMW.2010.5703906
P. Qian, G. Bai, Jie Zhao, Yiqin Wang
We performed metabolism studies on the urine specimens using gas chromatography-mass spectrometry (GC-MS) technology. Through comparing samples from patients with chronic renal failure and healthy control people, we evaluated the correlation of metabolic changes in urine with syndromes in Traditional Chinese Medicine (TCM) for patients with chronic renal failure. Methods ifty-four urine specimens from chronic renal failure patients and 25 urine specimens from healthy people were collected. After the specimens had silylation derivatization reaction with capric acid as the interior label and measured with GC-MS method, the spectrum was plotted.(1) After silylation derivatization reaction and GC-MS analysis, in the specimens from chronic renal failure and healthy control, 8 peaks were identified to be statistically different by 2-tailed 2-sample t-test (P<0.05). Based on the NIST spectral library, Mainlib database and Wiley database. There was a significant difference between the chronic renal failure group and healthy group. The identification results of the metabolic products were the same as those of hierarchical cluster analysis and principal component analysis.
{"title":"Metabonomics studies on urine specimens from patients with chronic renal failure","authors":"P. Qian, G. Bai, Jie Zhao, Yiqin Wang","doi":"10.1109/BIBMW.2010.5703906","DOIUrl":"https://doi.org/10.1109/BIBMW.2010.5703906","url":null,"abstract":"We performed metabolism studies on the urine specimens using gas chromatography-mass spectrometry (GC-MS) technology. Through comparing samples from patients with chronic renal failure and healthy control people, we evaluated the correlation of metabolic changes in urine with syndromes in Traditional Chinese Medicine (TCM) for patients with chronic renal failure. Methods ifty-four urine specimens from chronic renal failure patients and 25 urine specimens from healthy people were collected. After the specimens had silylation derivatization reaction with capric acid as the interior label and measured with GC-MS method, the spectrum was plotted.(1) After silylation derivatization reaction and GC-MS analysis, in the specimens from chronic renal failure and healthy control, 8 peaks were identified to be statistically different by 2-tailed 2-sample t-test (P<0.05). Based on the NIST spectral library, Mainlib database and Wiley database. There was a significant difference between the chronic renal failure group and healthy group. The identification results of the metabolic products were the same as those of hierarchical cluster analysis and principal component analysis.","PeriodicalId":158587,"journal":{"name":"BIBM Workshops","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":"127977986","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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