Pub Date : 2001-03-04DOI: 10.1109/BIBE.2001.974429
Michihiro Kuramochi, G. Karypis
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus to functional genomics. Functional genomics represents the next phase, that expands the biological investigation to studying the functionality of genes of a single organism as well as studying and correlating the functionality of genes across many different organisms. Recently developed methods for monitoring genome-wide mRNA expression changes hold the promise of allowing us to inexpensively gain insights into the function of unknown genes. In this paper we focus on evaluating the feasibility of using supervised machine learning methods for determining the function of genes based solely on their expression profiles. We experimentally evaluate the performance of traditional classification algorithms such as support vector machines and k-nearest neighbors on the yeast genome, and present new approaches for classification that improve the overall recall with moderate reductions in precision. Our experiments show that the accuracies achieved for different classes varies dramatically. In analyzing these results we show that the achieved accuracy is highly dependent on whether or not the genes of that class were significantly active during the various experimental conditions, suggesting that gene expression profiles can become a viable alternative to sequence similarity searches provided that the genes are observed under a wide range of experimental conditions.
{"title":"Gene classification using expression profiles: a feasibility study","authors":"Michihiro Kuramochi, G. Karypis","doi":"10.1109/BIBE.2001.974429","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974429","url":null,"abstract":"As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus to functional genomics. Functional genomics represents the next phase, that expands the biological investigation to studying the functionality of genes of a single organism as well as studying and correlating the functionality of genes across many different organisms. Recently developed methods for monitoring genome-wide mRNA expression changes hold the promise of allowing us to inexpensively gain insights into the function of unknown genes. In this paper we focus on evaluating the feasibility of using supervised machine learning methods for determining the function of genes based solely on their expression profiles. We experimentally evaluate the performance of traditional classification algorithms such as support vector machines and k-nearest neighbors on the yeast genome, and present new approaches for classification that improve the overall recall with moderate reductions in precision. Our experiments show that the accuracies achieved for different classes varies dramatically. In analyzing these results we show that the achieved accuracy is highly dependent on whether or not the genes of that class were significantly active during the various experimental conditions, suggesting that gene expression profiles can become a viable alternative to sequence similarity searches provided that the genes are observed under a wide range of experimental conditions.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127836820","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974414
R. Wong, William M. Shui
Biological databanks have proven useful to bioscience researchers, especially in the analysis of raw data. Computational tools for sequence identification, structural analysis, and visualization have been built to access these databanks. This paper describes a way to utilize these resources (both data and tools) by integrating different biological databanks into a unified XML framework. An interface to access the embedded bioinformatic tools for this common model is built by leveraging the query language of XML database management system. The proposed framework has been implemented with the emphasis of reusing the existing bioinformatic data and tools. This paper describes the overall architecture of this prototype and some design issues.
{"title":"Utilizing multiple bioinformatics information sources: an XML database approach","authors":"R. Wong, William M. Shui","doi":"10.1109/BIBE.2001.974414","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974414","url":null,"abstract":"Biological databanks have proven useful to bioscience researchers, especially in the analysis of raw data. Computational tools for sequence identification, structural analysis, and visualization have been built to access these databanks. This paper describes a way to utilize these resources (both data and tools) by integrating different biological databanks into a unified XML framework. An interface to access the embedded bioinformatic tools for this common model is built by leveraging the query language of XML database management system. The proposed framework has been implemented with the emphasis of reusing the existing bioinformatic data and tools. This paper describes the overall architecture of this prototype and some design issues.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115494060","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974437
L. M. Bates, R. Robb
Stereotactic navigational systems are being incorporated into an increasing number of neurosurgical procedures. Preoperatively acquired 3D images are used for planning the procedure, and are also employed in intraoperative navigations to help localize and resect brain lesions. However, as the operation progresses, multiple factors contribute to changes that limit the accuracy of the navigation based on pre-operative images alone. Our method to correct for brain shift involves the use of ultrasound intraoperatively to update patient specific pre-operative MRI scans using a physics based dynamic model. To validate the imaging and modeling process, a phantom was designed that simulates the brain and its shifting patterns resulting from several of the clinical factors present during a brain operation. MRI and ultrasound datasets were acquired for several permutations of phantom parameters. Deformation algorithms were then applied to the phantom data to demonstrate the efficacy of this approach as a method to effectively update the pre-operatively acquired MRI data during an operation.
{"title":"Investigation of ultrasound image based correction of intraoperative brain shift","authors":"L. M. Bates, R. Robb","doi":"10.1109/BIBE.2001.974437","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974437","url":null,"abstract":"Stereotactic navigational systems are being incorporated into an increasing number of neurosurgical procedures. Preoperatively acquired 3D images are used for planning the procedure, and are also employed in intraoperative navigations to help localize and resect brain lesions. However, as the operation progresses, multiple factors contribute to changes that limit the accuracy of the navigation based on pre-operative images alone. Our method to correct for brain shift involves the use of ultrasound intraoperatively to update patient specific pre-operative MRI scans using a physics based dynamic model. To validate the imaging and modeling process, a phantom was designed that simulates the brain and its shifting patterns resulting from several of the clinical factors present during a brain operation. MRI and ultrasound datasets were acquired for several permutations of phantom parameters. Deformation algorithms were then applied to the phantom data to demonstrate the efficacy of this approach as a method to effectively update the pre-operatively acquired MRI data during an operation.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131668265","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974426
John Bluis, Ravi Nori, Hsin-Wei Wang, Pinglei Zhou, J. Gogarten, Dong-Guk Shin
Scientists are able to use many different phylogenetic analysis tools to assist them in their research. The data collection and data analysis processes can take days or weeks to complete. Having this data available in a repository would reduce this process time and allow researchers to spend more time analyzing data instead of collecting it. We collected data for 21 completely sequenced genomes and created an intuitive interface for browsing the genomes. The interface allows users to search this data including the pre-calculated phylogenetic trees that are stored in the database. We have also developed a new method for comparing a large set of phylogenetic trees so users can search the database based on a user given hypothesis tree.
{"title":"Comparing trees in a phylogenetic relationship repository","authors":"John Bluis, Ravi Nori, Hsin-Wei Wang, Pinglei Zhou, J. Gogarten, Dong-Guk Shin","doi":"10.1109/BIBE.2001.974426","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974426","url":null,"abstract":"Scientists are able to use many different phylogenetic analysis tools to assist them in their research. The data collection and data analysis processes can take days or weeks to complete. Having this data available in a repository would reduce this process time and allow researchers to spend more time analyzing data instead of collecting it. We collected data for 21 completely sequenced genomes and created an intuitive interface for browsing the genomes. The interface allows users to search this data including the pre-calculated phylogenetic trees that are stored in the database. We have also developed a new method for comparing a large set of phylogenetic trees so users can search the database based on a user given hypothesis tree.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132552377","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974425
J. Quintero, A. Aguilera, M. Abraham, H. Villegas, G. Montilla, B. Solaiman
An overview is presented of different constraints in conventional medical decision-making for improving collaborative reasoning. When designing and implementing an effective assisted diagnoses system it is imperative to make a complete study of reasoning processes used by physicians every day. We are particularly interested in studying the process of conventional decision-making when, at the first stage, a physician faces a diagnosis decision and, later, when this decision is made by several physicians, that is, when collaborative medical reasoning is involved. The design of an architecture that supports the requirements of medical practices in this framework is presented.
{"title":"Medical decision-making and collaborative reasoning","authors":"J. Quintero, A. Aguilera, M. Abraham, H. Villegas, G. Montilla, B. Solaiman","doi":"10.1109/BIBE.2001.974425","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974425","url":null,"abstract":"An overview is presented of different constraints in conventional medical decision-making for improving collaborative reasoning. When designing and implementing an effective assisted diagnoses system it is imperative to make a complete study of reasoning processes used by physicians every day. We are particularly interested in studying the process of conventional decision-making when, at the first stage, a physician faces a diagnosis decision and, later, when this decision is made by several physicians, that is, when collaborative medical reasoning is involved. The design of an architecture that supports the requirements of medical practices in this framework is presented.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116168336","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974436
Francis K. H. Quek, R. Bryll, M. Harper, L. Chen, L. Ramig
Parkinson's disease (PD) belongs to a class of neurodegenerative diseases that affect both the patient's speech and motor capabilities. To date, PD diagnosis and the determination of disease progress and treatment efficacy is based entirely on the subjective observation of a trained physician. We present the results of a pilot study of two Idiopathic PD patients who have undergone Lee Silverman Voice Treatment (LSVT). It has been observed subjectively that gestural performance of patients improve in tandem with speech improvements after LSVT. It is hypothesized that these improvements are taking place at a neurological level. Measurements of speech and gesture suggest that LSVT improves the quality of both gesticulation and speech.
{"title":"Audio and vision-based evaluation of parkinson~s disease from discourse video","authors":"Francis K. H. Quek, R. Bryll, M. Harper, L. Chen, L. Ramig","doi":"10.1109/BIBE.2001.974436","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974436","url":null,"abstract":"Parkinson's disease (PD) belongs to a class of neurodegenerative diseases that affect both the patient's speech and motor capabilities. To date, PD diagnosis and the determination of disease progress and treatment efficacy is based entirely on the subjective observation of a trained physician. We present the results of a pilot study of two Idiopathic PD patients who have undergone Lee Silverman Voice Treatment (LSVT). It has been observed subjectively that gestural performance of patients improve in tandem with speech improvements after LSVT. It is hypothesized that these improvements are taking place at a neurological level. Measurements of speech and gesture suggest that LSVT improves the quality of both gesticulation and speech.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130369172","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974433
R. Gutierrez-Osuna, Nilesh U. Powar, P. Sun
This article presents a computational mechanism inspired by the process of chemosensory adaptation in the mammalian olfactory system. The algorithm operates on multiple subsets of the sensory space, generating a family of discriminant functions for different volatile compounds. A set of selectivity coefficients is associated to each discriminant function on the basis of its behavior in the presence of mixtures. These coefficients are employed to form a weighted average of the discriminant functions and establish a feedback signal that reduces the contribution of certain sensory inputs, inhibiting the overall selectivity of the system to previously detected analytes. The algorithm is validated on a database of organic solvents using an array of temperature-modulated metal-oxide chemoresistors.
{"title":"Chemosensory adaptation in an electronic nose","authors":"R. Gutierrez-Osuna, Nilesh U. Powar, P. Sun","doi":"10.1109/BIBE.2001.974433","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974433","url":null,"abstract":"This article presents a computational mechanism inspired by the process of chemosensory adaptation in the mammalian olfactory system. The algorithm operates on multiple subsets of the sensory space, generating a family of discriminant functions for different volatile compounds. A set of selectivity coefficients is associated to each discriminant function on the basis of its behavior in the presence of mixtures. These coefficients are employed to form a weighted average of the discriminant functions and establish a feedback signal that reduces the contribution of certain sensory inputs, inhibiting the overall selectivity of the system to previously detected analytes. The algorithm is validated on a database of organic solvents using an array of temperature-modulated metal-oxide chemoresistors.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115433141","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974418
Hsien-Da Huang, Shu-Fen Fang, Jorng-Tzong Horng, Cheng-Yan Kao
Some structural motifs, like tetra-loops, in ribosomal RNA are known to functionally implicate in virtually every aspect of protein synthesis. Our aim in this study is to discover common structural motifs (CSMs), which are related to specific domains or functions, within the secondary structures of ribosomal RNAs in a data set constructed. After applying data mining techniques to mine the common structural motifs, a machine learning approach is used to find significant discriminating common structural motifs from groups of organisms. By applying to several data sets constructed in this study, it suggests that the CSMs can provide effective information to classify organisms and help biologists understand the functions of ribosomal RNA. From the experiments of the classification of organisms and the construction of phylogenetic trees by CSMs mined, we find our approach is promising.
{"title":"Discovering common structural motifs from SSU 16 S ribosomal RNA secondary structures","authors":"Hsien-Da Huang, Shu-Fen Fang, Jorng-Tzong Horng, Cheng-Yan Kao","doi":"10.1109/BIBE.2001.974418","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974418","url":null,"abstract":"Some structural motifs, like tetra-loops, in ribosomal RNA are known to functionally implicate in virtually every aspect of protein synthesis. Our aim in this study is to discover common structural motifs (CSMs), which are related to specific domains or functions, within the secondary structures of ribosomal RNAs in a data set constructed. After applying data mining techniques to mine the common structural motifs, a machine learning approach is used to find significant discriminating common structural motifs from groups of organisms. By applying to several data sets constructed in this study, it suggests that the CSMs can provide effective information to classify organisms and help biologists understand the functions of ribosomal RNA. From the experiments of the classification of organisms and the construction of phylogenetic trees by CSMs mined, we find our approach is promising.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128442817","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974439
Deacon J. Sweeney, G. Alter, M. Raymer, T. Doom
Sequencing of the human genome was a great stride towards modeling cellular complexes, massive systems whose key players are proteins and DNA. A major bottleneck limiting the modeling process is structure and function annotation for the new genes. Contemporary protein structure prediction algorithms represent the sequence of every protein of known structure with a profile to which the profile of a protein sequence of unknown structure is compared for recognition. We propose a novel approach to increase the scope and resolution of protein structure profiles. Our technique locates equivalent regions among the members of a structurally similar fold family, and clusters these region by structural similarity. Equivalent substructures can then be swapped on the common regions to generate an array of profiles which represent hypothetical structures to supplement profiles of known structures. Strategies for a specific implementation of the strategy are discussed, including application to multiple template comparative modeling.
{"title":"Profile combinatorics for fragment selection in comparative protein structure modeling","authors":"Deacon J. Sweeney, G. Alter, M. Raymer, T. Doom","doi":"10.1109/BIBE.2001.974439","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974439","url":null,"abstract":"Sequencing of the human genome was a great stride towards modeling cellular complexes, massive systems whose key players are proteins and DNA. A major bottleneck limiting the modeling process is structure and function annotation for the new genes. Contemporary protein structure prediction algorithms represent the sequence of every protein of known structure with a profile to which the profile of a protein sequence of unknown structure is compared for recognition. We propose a novel approach to increase the scope and resolution of protein structure profiles. Our technique locates equivalent regions among the members of a structurally similar fold family, and clusters these region by structural similarity. Equivalent substructures can then be swapped on the common regions to generate an array of profiles which represent hypothetical structures to supplement profiles of known structures. Strategies for a specific implementation of the strategy are discussed, including application to multiple template comparative modeling.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115066600","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 : 2001-03-04DOI: 10.1109/BIBE.2001.974409
Crispin J. Miller, T. Attwood
Whole genome comparison and clustering cannot be routinely performed without access to significant resources. If as expected, repositories continue to grow at the current rate, increasingly large and expensive systems will be required in order to maintain the status quo. The high-proportion of uncharacterised gene-sequences, combined with the fact that the majority of sequence analysis techniques are alignment-based, raises the possibility that alternative approaches might be able to identify relationships that have otherwise been missed. There is a need for alternative ways to predict function. PSST is an analysis tool with parallels to both pairwise algorithms and multiple motif-based pattern approaches. It is significantly faster than BLAST, and for some families including GPCRs, the tool is more sensitive and selective as well. For others it is worse. This paper describes the algorithm, its implementation, its evaluation against a diverse set of protein families, and discusses the reasons behind its behaviour.
{"title":"PSST... the probabilistic sequence search tool","authors":"Crispin J. Miller, T. Attwood","doi":"10.1109/BIBE.2001.974409","DOIUrl":"https://doi.org/10.1109/BIBE.2001.974409","url":null,"abstract":"Whole genome comparison and clustering cannot be routinely performed without access to significant resources. If as expected, repositories continue to grow at the current rate, increasingly large and expensive systems will be required in order to maintain the status quo. The high-proportion of uncharacterised gene-sequences, combined with the fact that the majority of sequence analysis techniques are alignment-based, raises the possibility that alternative approaches might be able to identify relationships that have otherwise been missed. There is a need for alternative ways to predict function. PSST is an analysis tool with parallels to both pairwise algorithms and multiple motif-based pattern approaches. It is significantly faster than BLAST, and for some families including GPCRs, the tool is more sensitive and selective as well. For others it is worse. This paper describes the algorithm, its implementation, its evaluation against a diverse set of protein families, and discusses the reasons behind its behaviour.","PeriodicalId":405124,"journal":{"name":"Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)","volume":"8 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134056914","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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