Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP...Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP), is useful for its high heuristic ability as a search method for obtaining suitable solutions expressed as tree structures. However, because GP determines the values of parameters such as coefficients by random values, it is difficult to apply in the inference of state equations that describe oscillatory biochemical reaction systems with high nonlinearity. Accordingly, in this study, we propose a new GP procedure called “k-step GP” intended for inferring the state equations of oscillatory biochemical reaction systems. The k-step GP procedure consists of two algorithms: 1) Parameter optimization using the modified Powell method—after genetic operations such as crossover and mutation, the values of parameters such as coefficients are optimized by applying the modified Powell method with secondary convergence. 2) GP using divided learning data—to improve the inference efficiency, imposes perturbations through the addition of learning data at various intervals and adaptations to these changes result in state equations with higher fitness. We are confident that k-step GP is an algorithm that is particularly well suited to inferring state equations for oscillatory biochemical reaction systems and contributes to solving inverse problems in systems biology.展开更多
Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific dis...Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific discovery task,and has been demonstrated to possess the priming effect,which is attributed to the regularity identification and its subsequent extrapolation.In order to reduce the heterogeneities and make the experimental task proper for a brain imaging study,the number magnitude and arithmetic operation involved in number series completion tasks are further restricted.Behavioral performance in Experiment 1 shows the reliable priming effect for targets as expected.Then,a factorial design (the priming effect:prime vs.target;the period length:simple vs.complex) of event-related functional magnetic resonance imaging (fMRI) is used in Experiment 2 to examine the neural basis of data-driven scientific discovery.The fMRI results reveal a double dissociation of the left DLPFC (dorsolateral prefrontal cortex) and the left APFC (anterior prefrontal cortex) between the simple (period length=1) and the complex (period length=2) number series completion task.The priming effect in the left DLPFC is more significant for the simple task than for the complex task,while the priming effect in the left APFC is more significant for the complex task than for the simple task.The reliable double dissociation may suggest the different roles of the left DLPFC and left APFC in data-driven scientific discovery.The left DLPFC (BA 46) may play a crucial role in rule identification,while the left APFC (BA 10) may be related to mental set maintenance needed during rule identification and extrapolation.展开更多
Literature searches on the Web result in great volumes of query results. A model is presented here to refine the search process using user interests. User interests are analyzed to calculate semantic similarity among ...Literature searches on the Web result in great volumes of query results. A model is presented here to refine the search process using user interests. User interests are analyzed to calculate semantic similarity among the interest terms to refine the query. Traditional general purpose similarity measures may not always fit a domain specific context. This paper presents a similarity method for medical literature searches based on the biomedical literature knowledge source ＂MEDLINE＂, the normalized MEDLINE distance, to more reasonably reflect the relevance between medical terms. This measure gives more accurate user interest descriptions through calculating the similarities of user interest terms to rerank the interest term list. The accurate user interest descriptions can be used for query refinement in keyword searches to give more personalized results for the user. This measure also improves the search results for personalization through controlling the return number of results on each topic of interest.展开更多
Previous studies have focused on changes in cerebral cortex activity accompanying memory formation and consolidation.Although the role of the parietal cortex in memory retrieval is well established,it is not well unde...Previous studies have focused on changes in cerebral cortex activity accompanying memory formation and consolidation.Although the role of the parietal cortex in memory retrieval is well established,it is not well understood how parietal cortex memory consolidation for mathematical rules is related to granularity of stored information(i.e.,degree of detail or precision).Changes in parietal cortex activity associated with memory consolidation were analyzed using the Ebbinghaus paradigm and functional magnetic resonance imaging(fMRI).Over the course of 1 week,participants learned Boolean arithmetic tasks involving stimulus-response mapping rules containing either low-or high-granularity information.FMRI images were collected on day 1(i.e., low-granularity condition)and day 7(i.e.,high-granularity condition).The present data suggested that with practice,stored information was converted from a low-granularity to a high-granularity form.By following rule learning,it was hypothesized that the process of consolidation would involve an increased degree of rule representation granularity.Evidence for this process was reflected in parietal cortex activity.This finding was consistent with the hypothesis that mnemonic reconstruction in the parietal cortex is required for memory consolidation,and results suggested that information granules are formed during memory consolidation.The present results could increase the understanding of the relationship between memory consolidation and information granularity.展开更多
The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic emergency.Culture and anti-epidemic policy do not necessarily conf...The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic emergency.Culture and anti-epidemic policy do not necessarily conflict with each other.All countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcome this historically tragic pandemic together.展开更多
文摘Systems biology requires the development of algorithms that use omics data to infer interaction networks among biomolecules working within an organism. One major type of evolutionary algorithm, genetic programming (GP), is useful for its high heuristic ability as a search method for obtaining suitable solutions expressed as tree structures. However, because GP determines the values of parameters such as coefficients by random values, it is difficult to apply in the inference of state equations that describe oscillatory biochemical reaction systems with high nonlinearity. Accordingly, in this study, we propose a new GP procedure called “k-step GP” intended for inferring the state equations of oscillatory biochemical reaction systems. The k-step GP procedure consists of two algorithms: 1) Parameter optimization using the modified Powell method—after genetic operations such as crossover and mutation, the values of parameters such as coefficients are optimized by applying the modified Powell method with secondary convergence. 2) GP using divided learning data—to improve the inference efficiency, imposes perturbations through the addition of learning data at various intervals and adaptations to these changes result in state equations with higher fitness. We are confident that k-step GP is an algorithm that is particularly well suited to inferring state equations for oscillatory biochemical reaction systems and contributes to solving inverse problems in systems biology.
基金supported by the National Natural Science Foundation of China (Grant Nos.60775039 and 60875075)supported by the Grant-in-aid for Scientific Research (Grant No.18300053) from the Japanese Society for the Promotion of Science+2 种基金Support Center for Advanced Telecommunications Technology Research,Foundationthe Open Foundation of Key Laboratory of Multimedia and Intelligent Software Technology (Beijing University of Technology) Beijingthe Doctoral Research Fund of Beijing University of Technology (Grant No.00243)
文摘Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific discovery task,and has been demonstrated to possess the priming effect,which is attributed to the regularity identification and its subsequent extrapolation.In order to reduce the heterogeneities and make the experimental task proper for a brain imaging study,the number magnitude and arithmetic operation involved in number series completion tasks are further restricted.Behavioral performance in Experiment 1 shows the reliable priming effect for targets as expected.Then,a factorial design (the priming effect:prime vs.target;the period length:simple vs.complex) of event-related functional magnetic resonance imaging (fMRI) is used in Experiment 2 to examine the neural basis of data-driven scientific discovery.The fMRI results reveal a double dissociation of the left DLPFC (dorsolateral prefrontal cortex) and the left APFC (anterior prefrontal cortex) between the simple (period length=1) and the complex (period length=2) number series completion task.The priming effect in the left DLPFC is more significant for the simple task than for the complex task,while the priming effect in the left APFC is more significant for the complex task than for the simple task.The reliable double dissociation may suggest the different roles of the left DLPFC and left APFC in data-driven scientific discovery.The left DLPFC (BA 46) may play a crucial role in rule identification,while the left APFC (BA 10) may be related to mental set maintenance needed during rule identification and extrapolation.
基金Supported by the European Commission under the 7th Framework Programme,the Large Knowledge Collider (LarKC) Project (No.FP7-215535)
文摘Literature searches on the Web result in great volumes of query results. A model is presented here to refine the search process using user interests. User interests are analyzed to calculate semantic similarity among the interest terms to refine the query. Traditional general purpose similarity measures may not always fit a domain specific context. This paper presents a similarity method for medical literature searches based on the biomedical literature knowledge source ＂MEDLINE＂, the normalized MEDLINE distance, to more reasonably reflect the relevance between medical terms. This measure gives more accurate user interest descriptions through calculating the similarities of user interest terms to rerank the interest term list. The accurate user interest descriptions can be used for query refinement in keyword searches to give more personalized results for the user. This measure also improves the search results for personalization through controlling the return number of results on each topic of interest.
基金supported by the National Natural Science Foundation of China(60673015,60775039 and 08BTQ024)the Grant-in-aid for Scientific Research(18300053)from the Japanese Ministry of Education,Culture,Sports,Science and Technology
文摘Previous studies have focused on changes in cerebral cortex activity accompanying memory formation and consolidation.Although the role of the parietal cortex in memory retrieval is well established,it is not well understood how parietal cortex memory consolidation for mathematical rules is related to granularity of stored information(i.e.,degree of detail or precision).Changes in parietal cortex activity associated with memory consolidation were analyzed using the Ebbinghaus paradigm and functional magnetic resonance imaging(fMRI).Over the course of 1 week,participants learned Boolean arithmetic tasks involving stimulus-response mapping rules containing either low-or high-granularity information.FMRI images were collected on day 1(i.e., low-granularity condition)and day 7(i.e.,high-granularity condition).The present data suggested that with practice,stored information was converted from a low-granularity to a high-granularity form.By following rule learning,it was hypothesized that the process of consolidation would involve an increased degree of rule representation granularity.Evidence for this process was reflected in parietal cortex activity.This finding was consistent with the hypothesis that mnemonic reconstruction in the parietal cortex is required for memory consolidation,and results suggested that information granules are formed during memory consolidation.The present results could increase the understanding of the relationship between memory consolidation and information granularity.
基金This research was funded by the National Natural Science Foundation of China no.71932008 and no.91546201.
文摘The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic emergency.Culture and anti-epidemic policy do not necessarily conflict with each other.All countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcome this historically tragic pandemic together.
