The research on graph pattern matching(GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM th...The research on graph pattern matching(GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM this paper is to make a breast cancer-oriented diagnosis before the surgery. Technically, this paper has firstly made a new definition of GPM, aiming to explore the GPM in the medical field, especially in Medical Knowledge Graphs(MKGs). Then, in the specific matching process, this paper introduces fuzzy calculation, and proposes a multi-threaded bidirectional routing exploration(M-TBRE) algorithm based on depth first search and a two-way routing matching algorithm based on multi-threading. In addition, fuzzy constraints are introduced in the M-TBRE algorithm, which leads to the Fuzzy-M-TBRE algorithm. The experimental results on the two datasets show that compared with existing algorithms, our proposed algorithm is more efficient and effective.展开更多
Freshwater ecosystems harbor a vast diversity of micro-eukaryotes(rotifers,crustaceans and protists),and such diverse taxonomic groups play important roles in ecosystem functioning and services.Unfortunately,freshwate...Freshwater ecosystems harbor a vast diversity of micro-eukaryotes(rotifers,crustaceans and protists),and such diverse taxonomic groups play important roles in ecosystem functioning and services.Unfortunately,freshwater ecosystems and biodiversity therein are threatened by many environmental stressors,particularly those derived from intensive human activities such as chemical pollution.In the past several decades,significant efforts have been devoted to halting biodiversity loss to recover services and functioning of freshwater ecosystems.Biodiversity monitoring is the first and a crucial step towards diagnosing pollution impacts on ecosystems and making conservation plans.Yet,bio-monitoring of ubiquitous micro-eukaryotes is extremely challenging,owing to many technical issues associated with micro-zooplankton such as microscopic size,fuzzy morphological features,and extremely high biodiversity.Here,we review current methods used for monitoring zooplankton biodiversity to advance management of impaired freshwater ecosystems.We discuss the development of traditional morphologybased identification methods such as scanning electron microscope(SEM)and ZOOSCAN and FlowCAM automatic systems,and DNA-based strategies such as metabarcoding and real-time quantitative PCR.In addition,we summarize advantages and disadvantages of these methods when applied for monitoring impacted ecosystems,and we propose practical DNA-based monitoring workflows for studying biological consequences of environmental pollution in freshwater ecosystems.Finally,we propose possible solutions for existing technical issues to improve accuracy and efficiency of DNA-based biodiversity monitoring.展开更多
基金supported by the National Natural Science Foundation of China under grants 62076087&61906059the Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT)of the Ministry of Education of China under grant IRT17R32
文摘The research on graph pattern matching(GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM this paper is to make a breast cancer-oriented diagnosis before the surgery. Technically, this paper has firstly made a new definition of GPM, aiming to explore the GPM in the medical field, especially in Medical Knowledge Graphs(MKGs). Then, in the specific matching process, this paper introduces fuzzy calculation, and proposes a multi-threaded bidirectional routing exploration(M-TBRE) algorithm based on depth first search and a two-way routing matching algorithm based on multi-threading. In addition, fuzzy constraints are introduced in the M-TBRE algorithm, which leads to the Fuzzy-M-TBRE algorithm. The experimental results on the two datasets show that compared with existing algorithms, our proposed algorithm is more efficient and effective.
基金supported by the National Natural Science Foundation of China[grant numbers 31800307,31572228]National Key R&D Program of China[grant number 2016YFC0500406]Chinese Academy of Science[grant number ZDRW-ZS-2016-5-6].
文摘Freshwater ecosystems harbor a vast diversity of micro-eukaryotes(rotifers,crustaceans and protists),and such diverse taxonomic groups play important roles in ecosystem functioning and services.Unfortunately,freshwater ecosystems and biodiversity therein are threatened by many environmental stressors,particularly those derived from intensive human activities such as chemical pollution.In the past several decades,significant efforts have been devoted to halting biodiversity loss to recover services and functioning of freshwater ecosystems.Biodiversity monitoring is the first and a crucial step towards diagnosing pollution impacts on ecosystems and making conservation plans.Yet,bio-monitoring of ubiquitous micro-eukaryotes is extremely challenging,owing to many technical issues associated with micro-zooplankton such as microscopic size,fuzzy morphological features,and extremely high biodiversity.Here,we review current methods used for monitoring zooplankton biodiversity to advance management of impaired freshwater ecosystems.We discuss the development of traditional morphologybased identification methods such as scanning electron microscope(SEM)and ZOOSCAN and FlowCAM automatic systems,and DNA-based strategies such as metabarcoding and real-time quantitative PCR.In addition,we summarize advantages and disadvantages of these methods when applied for monitoring impacted ecosystems,and we propose practical DNA-based monitoring workflows for studying biological consequences of environmental pollution in freshwater ecosystems.Finally,we propose possible solutions for existing technical issues to improve accuracy and efficiency of DNA-based biodiversity monitoring.
