Browsing by Author "Tsai, Chia-Ta"

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Designing predictors of DNA-binding proteinsusing an efficient physicochemical propertymining method
(2010-01-01)
Lin, Yih-Jer
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Tsai, Chia-Ta
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Hol, Shinn-Ying
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Tsai, Chia-Ta
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Huang, Hui-Ling
DNA-binding proteins play a pivotal role in various intra-and extra-cellular activities ranging from DNA replicationto gene expression control. Many researches mainly focused on prediction and analysis of protein binding sites in DNA. We are interested in predicting binding and non-binding proteins from protein sequences. Physicochemical properties are well recognized to be effective in designing various predictors for understanding the functions and characteristics of proteins. Generally, the domain knowledge of proteins to be analyzed from biologists is needed to select effective physicochemical properties. In this study, we propose an efficient method for designing predictors of binding and non-binding proteins using a set of informative physicochemical properties obtained from an inheritable bi-objective genetic algorithm without using the domain knowledge of binding and non-binding proteins. Three benchmark datasets were used to evaluate the proposed method using SVM and informative physicochemical properties as the features. The prediction accuracy of independent test is close to 80.0%. From the analysis of informative physicochemical properties, some knowledge of binding and non-binding proteins can be further investigated. The proposed physicochemical property mining method can be used conveniently as the core for designing predictors for various DNA-binding problems.
Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties
(2011-02-15)
Huang, Hui-Lin
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Lin, I-Che
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Liou, Yi-Fan
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Tsai, Chia-Ta
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Hsu, Kai-Ti
Background: Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results: This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der Waals volume, pK (pK-C, pK-N, pK-COOH and pK-a(RCOOH)), etc. Conclusions: The proposed approach Auto-IDPCPs would help designers to investigate informative physicochemical and biochemical properties by considering both prediction accuracy and analysis of binding mechanism simultaneously. The approach Auto-IDPCPs can be also applicable to predict and analyze other protein functions from sequences.
Serum C-reactive protein and procalcitonin values in acute Q fever, scrub typhus, and murine typhus
(2020-05-12)
Lin, I-Fan
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Lin, Jiun-Nong
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Tsai, Chia-Ta
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Wu, Yu-Ying
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Chen, Yen-Hsu
BackgroundAlthough C-reactive protein (CRP) and procalcitonin (PCT) are widely used inflammatory markers for infectious diseases, their role and potential application for rickettsioses were rarely studied.MethodsA retrospective chart review and serological study were conducted in patients with rickettsioses. The clinical presentations, characteristics, laboratory data, and treatment responses were recorded and their associations with CRP and PCT values were analyzed.ResultsA total of 189 cases of rickettsioses, including 115 cases of acute Q fever (60.8%), 55 cases of scrub typhus (29.1%), and 19 cases of murine typhus (10.1%) were investigated. Both CRP and PCT values increased in the acute phase and declined in the convalescent phase. In the acute phase, mean CRP and PCT values were 78.263.7mg/L and 1.05 +/- 1.40ng/mL, respectively. Percentages of patients falling under different cut-off values of CRP and PCT were calculated systematically. Only 10.8% of CRP was >150mg/L and 14.2% of PCT was >2.0ng/mL. Patients with delayed responses to doxycycline treatment (>3days from treatment to defervescence) had significantly higher CRP values (102.7 +/- 77.1 vs. 72.2 +/- 58.2mg/L, p =0.041) and more PCT >1.0ng/ml (48.4% vs. 26.0%, p =0.019) in the acute phase; higher CRP values (19.1 +/- 37.4 vs. 3.6 +/- 13.1mg/L, p =0.049) and more PCT >0.5ng/ml (19.2% vs. 1.4%, p =0.005) in the convalescent phase. Correlation analysis was conducted for patients with acute Q fever. CRP and PCT values were positively correlated to each other, and both markers also had a positive correlation with serum aspartate transaminase values. Both CRP and PCT values and white blood cell counts were positively correlated to the days needed from doxycycline treatment to defervescence.Conclusion p id=Par CRP and PCT values might be useful in clinical investigations for patients with suspected rickettsioses and in predicting the response to doxycycline treatment for rickettsioses.
The epidemiology, characteristics and outbreaks of human leptospirosis and the association with animals in Taiwan, 2007-2014: A nationwide database study
(1970-01-01)
Tsai, Chia-Ta
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Lin, Jiun-Nong
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Lee, Chen-Hsiang
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Sun, Wu
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Chang, Yi-Chin
Background Leptospirosis (LS) is a neglected tropical zoonosis of global importance. A nationwide investigation of characteristics, epidemiology, risk factors and outbreak is crucial for awareness of this disease. Methods A nationwide database of reported LS cases from October 2007 to December 2014 obtained from the Centers for Disease Control, Taiwan, was analysed. Geographic information system software was used to map the distribution of confirmed LS cases and pigs. Cross-matching with the databases of Q fever, scrub typhus and murine typhus was conducted to identify possible coinfections. Results A total of 10,917 reported cases of LS were recorded in the database, which included 665 (6.1%) confirmed LS and 10,252 (93.9%) non-confirmed LS cases. The major residences of confirmed LS were the Kaohsiung-Pingtung (248, 37.3%) and Taipei (174, 26.2%) regions. The average annual incidence was 0.4/100,000 people. Compared with non-confirmed LS cases, confirmed LS cases had significantly higher percentages of male gender (83.6% vs. 67.9%, p < .001), high-risk occupations (farmer, animal husbandry or veterinarian) (24.8% vs. 13.7%, p < .001), residence in the Kaohsiung-Pingtung region (37.3% vs. 19.6%, p < .001) and exposure to rats (8.6% vs. 4.9%, p = .001) or pigs (9.4% vs. 1.9%, p < .001) but a lower mean age (47.8 +/- 15.1 vs. 51.+/- 18.5 years old). Rat and pig exposure trends were found in the northern and southern regions, respectively. Distribution of LS was consistent with pigs, and one outbreak associated with flooding and pigs occurred in the Pingtung region in 2009. Twenty-three and four patients with LS were coinfected with scrub typhus and Q fever, respectively. Conclusions LS is an endemic disease in Taiwan, particularly in the Kaohsiung-Pingtung and Taipei regions. High-risk occupations and animal exposure history are important for the clinical presumptive diagnosis of LS, particularly for rats in northern Taiwan and pigs in southern Taiwan. Although uncommon, clinicians should be aware of coinfection of LS with endemic rickettsial diseases.