scholarly journals MeSHHeading2vec: A new method for representing MeSH headings as feature vectors based on graph embedding algorithm

2019 ◽  
Author(s):  
Zhen-Hao Guo ◽  
Zhu-Hong You ◽  
Hai-Cheng Yi ◽  
Kai Zheng ◽  
Yan-Bin Wang

AbstractMotivationEffectively representing the MeSH headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify.ResultsIn this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships) which can be constructed by the rule of tree num. Then, five graph embedding algorithms including DeepWalk (DW), LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed method, we carried out the node classification and relationship prediction tasks. The experimental results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the distinguishable ability of vectors. Thus, it can act as input and continue to play a significant role in any disease-, drug-, microbe- and etc.-related computational models. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network [email protected]

Author(s):  
Zhen-Hao Guo ◽  
Zhu-Hong You ◽  
De-Shuang Huang ◽  
Hai-Cheng Yi ◽  
Kai Zheng ◽  
...  

Abstract Effectively representing Medical Subject Headings (MeSH) headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify. In this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships), which can be constructed by the tree num. Then, five graph embedding algorithms including DeepWalk, LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed methods, we carried out the node classification and relationship prediction tasks. The results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the representation ability of vectors. Thus, it can serve as an input and continue to play a significant role in any computational models related to disease, drug, microbe, etc. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network perspective.


2020 ◽  
Vol 27 (5) ◽  
pp. 385-391
Author(s):  
Lin Zhong ◽  
Zhong Ming ◽  
Guobo Xie ◽  
Chunlong Fan ◽  
Xue Piao

: In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well as many other processes. Surprisingly, lncRNA has an inseparable relationship with human diseases such as cancer. Therefore, only by knowing more about the function of lncRNA can we better solve the problems of human diseases. However, lncRNAs need to bind to proteins to perform their biomedical functions. So we can reveal the lncRNA function by studying the relationship between lncRNA and protein. But due to the limitations of traditional experiments, researchers often use computational prediction models to predict lncRNA protein interactions. In this review, we summarize several computational models of the lncRNA protein interactions prediction base on semi-supervised learning during the past two years, and introduce their advantages and shortcomings briefly. Finally, the future research directions of lncRNA protein interaction prediction are pointed out.


Author(s):  
Tatiani De Azevedo Lobo ◽  
Marli M. Moraes Da Costa

Resumo: O presente ensaio busca apresentar e fomentar algumas questões pertinentes ao debate contemporâneo sobre a pobreza, demonstrando a importância do tema no cenário mundial. Para tanto, inicialmente discorre-se sobre a construção histórico-social da pobreza e suas características contemporâneas. Com efeito, aponta-se a limitação dos fatores tradicionalmente apresentados como causadores da pobreza, como cultura, genética, geografia etc. Além disso, apresentam-se as formas atuais de monitorar o fenômeno, como o coeficiente de Gini e o IDH. Posteriormente, aborda-se a distribuição mundial da pobreza. Nesse ponto, colaciona-se que a pobreza é um problema mundial. No entanto, é perceptível que o Sul ainda concentra maior número de indivíduos pobres do que o Norte. Na esteira dos últimos dados da pesquisa realizada pelas Nações Unidas, houve uma nítida ascensão do Sul, especialmente nos indicadores sociais ligados à educação. A seguir, trata-se do capital social e da Teoria das Capacidades, apresentando-se novas abordagens da pobreza. Assim, o capital social trata de uma ideia utilizada para verificar a rede de relacionamento dos indivíduos. Já a Teoria das Capacidades está ligada com a ideia de oportunidade da liberdade. Por fim, estuda-se as políticas públicas, bem como seu aspecto fragmentário. Conclui-se, assim, sobre a necessidade de implementação de políticas públicas elaboradas sob a égide de novos paradigmas, a fim de possibilitar o tratamento específico do fenômeno da pobreza, conforme as peculiaridades de cada local. Para tanto foi utilizado neste trabalho o método de abordagem hipotético-dedutivo, o método de procedimento monográfico e a técnica de pesquisa, operacionalizados por meio do emprego de vasta pesquisa bibliográfica. Abstract: This essay seeks to provide and foster some relevant to the contemporary debate on poverty issues, demonstrating the importance of the issue on the world stage. For this purpose, initially spoke about the historical and social construction of poverty and its contemporary features. Indeed, he pointed out the limitation of the factors traditionally presented as the cause of poverty, as a culture, genetics, geography, etc. Furthermore, we presented the current ways of monitoring the phenomenon, such as the Gini coefficient and the HDI. Subsequently addressed the global distribution of poverty. At this point, if collated that poverty is a worldwide problem. However, it is apparent that the South still more concentrated than the poor North individuals. In the wake of recent data from research conducted by the United Nations, there was a sharp rise in the South, especially in social indicators related to education. Next, we treated the capital and the Theory of Capabilities, presenting new approaches to poverty. Thus, social capital is an idea used to verify the relationship network of individuals. Already Capabilities Theory is linked with the idea of freedom of opportunity. Finally, we studied public policy, as well as its fragmentary appearance. Thus, it is concluded on the need to implement public policies prepared under the aegis of new paradigms to enable specific treatment of the phenomenon of poverty, according to the peculiarities of each site. For that was used in this work the method of hypothetical-deductive approach, the method of procedure and the monographic research technique, operationalized through the use of extensive academic research.


2021 ◽  
pp. 194173812199938
Author(s):  
Gabor Schuth ◽  
Gyorgy Szigeti ◽  
Gergely Dobreff ◽  
Peter Revisnyei ◽  
Alija Pasic ◽  
...  

Background: Previous studies have examined the relationship between external training load and creatine kinase (CK) response after soccer matches in adults. This study aimed to build training- and match-specific CK prediction models for elite youth national team soccer players. Hypothesis: Training and match load will have different effects on the CK response of elite youth soccer players, and there will be position-specific differences in the most influential external and internal load parameters on the CK response. Study Design: Prospective cohort study. Level of Evidence: Level 4. Methods: Forty-one U16-U17 youth national team soccer players were measured over an 18-month period. Training and match load were monitored with global positioning system devices. Individual CK values were measured from whole blood every morning in training camps. The dataset consisted of 1563 data points. Clustered prediction models were used to examine the relationship between external/internal load and consecutive CK changes. Clusters were built based on the playing position and activity type. The performance of the linear regression models was described by the R2 and the root-mean-square error (RMSE, U/L for CK values). Results: The prediction models fitted similarly during games and training sessions ( R2 = 0.38-0.88 vs 0.6-0.77), but there were large differences based on playing positions. In contrast, the accuracy of the models was better during training sessions (RMSE = 81-135 vs 79-209 U/L). Position-specific differences were also found in the external and internal load parameters, which best explained the CK changes. Conclusion: The relationship between external/internal load parameters and CK changes are position specific and might depend on the type of session (training or match). Morning CK values also contributed to the next day’s CK values. Clinical Relevance: The relationship between position-specific external/internal load and CK changes can be used to individualize postmatch recovery strategies and weekly training periodization with a view to optimize match performance.


Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 974
Author(s):  
Hayfa Sharif ◽  
Caroline L. Hoad ◽  
Nichola Abrehart ◽  
Penny A. Gowland ◽  
Robin C. Spiller ◽  
...  

Background: Functional constipation in children is common. Management of this condition can be challenging and is often based on symptom reports. Increased, objective knowledge of colonic volume changes in constipation compared to health could provide additional information. However, very little data on paediatric colonic volume is available except from methods that are invasive or require unphysiological colonic preparations. Objectives: (1) To measure volumes of the undisturbed colon in children with functional constipation (FC) using magnetic resonance imaging (MRI) and provide initial normal range values for healthy controls, and (2) to investigate possible correlation of colonic volume with whole gut transit time (WGTT). Methods: Total and regional (ascending, transverse, descending, sigmoid, and rectum) colon volumes were measured from MRI images of 35 participants aged 7–18 years (16 with FC and 19 healthy controls), and corrected for body surface area. Linear regression was used to explore the relationship between total colon volume and WGTT. Results: Total colonic volume was significantly higher, with a median (interquartile range) of 309 mL (243–384 mL) for the FC group than for the healthy controls of 227 mL (180–263 mL). The largest increase between patients and controls was in the sigmoid colon–rectum region. In a linear regression model, there was a positive significant correlation between total colonic volume and WGTT (R = 0.56, p = 0.0005). Conclusions: This initial study shows increased volumes of the colon in children with FC, in a physiological state, without use of any bowel preparation. Increased knowledge of colonic morphology may improve understanding of FC in this age group and help to direct treatment.


Author(s):  
Victor Ei-Wen Lo ◽  
Yi-Chen Chiu ◽  
Hsin-Hung Tu

Background: There are different types of hand motions in people’s daily lives and working environments. However, testing duration increases as the types of hand motions increase to build a normative database. Long testing duration decreases the motivation of study participants. The purpose of this study is to propose models to predict pinch and press strength using grip strength. Methods: One hundred ninety-eight healthy volunteers were recruited from the manufacturing industries in Central Taiwan. The five types of hand motions were grip, lateral pinch, palmar pinch, thumb press, and ball of thumb press. Stepwise multiple linear regression was used to explore the relationship between force type, gender, height, weight, age, and muscle strength. Results: The prediction models developed according to the variable of the strength of the opposite hand are good for explaining variance (76.9–93.1%). Gender is the key demographic variable in the predicting models. Grip strength is not a good predictor of palmar pinch (adjusted-R2: 0.572–0.609), nor of thumb press and ball of thumb (adjusted-R2: 0.279–0.443). Conclusions: We recommend measuring the palmar pinch and ball of thumb strength and using them to predict the other two hand motions for convenience and time saving.


Author(s):  
Hua Li ◽  
Qingqing Lou ◽  
Qiubai Sun ◽  
Bowen Li

In order to solve the conflict of interests of institutional investors, this paper uses evolutionary game model. From the point of view of information sharing, this paper discusses four different situations. Only when the sum of risk and cost is less than the penalty of free riding, the evolution of institutional investors will eventually incline to the stable state of information sharing. That is, the phenomenon of hugging. The research shows that the institutional investors are not independent of each other, but the relationship network of institutional investors for the purpose of information exchange. The content of this paper enriches the research on information sharing of institutional investors.


Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 79 ◽  
Author(s):  
Xiaoyu Han ◽  
Yue Zhang ◽  
Wenkai Zhang ◽  
Tinglei Huang

Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to be helpful in relation extraction. Additional information such as entity type getting by NER (Named Entity Recognition) and description provided by knowledge base both have their limitations. Nevertheless, there exists another way to provide additional information which can overcome these limitations in Chinese relation extraction. As Chinese characters usually have explicit meanings and can carry more information than English letters. We suggest that characters that constitute the entities can provide additional information which is helpful for the relation extraction task, especially in large scale datasets. This assumption has never been verified before. The main obstacle is the lack of large-scale Chinese relation datasets. In this paper, first, we generate a large scale Chinese relation extraction dataset based on a Chinese encyclopedia. Second, we propose an attention-based model using the characters that compose the entities. The result on the generated dataset shows that these characters can provide useful information for the Chinese relation extraction task. By using this information, the attention mechanism we used can recognize the crucial part of the sentence that can express the relation. The proposed model outperforms other baseline models on our Chinese relation extraction dataset.


2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Jun Long ◽  
Lei Zhu ◽  
Zhan Yang ◽  
Chengyuan Zhang ◽  
Xinpan Yuan

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.


2017 ◽  
Author(s):  
Benjamin Davies

Computer simulation is a tool increasingly used by archaeologists to build theories about past human activity; however, simulation has had a limited role theorising about the relationship between past behaviours and the formation of observed patterning in the material record. This paper visits the argument for using simulation as a means of addressing the gap that exists between archaeological interpretations of past behaviours and their physical residues. It is argued that simulation is used for much the same reason that archaeologists use ethnographic or experimental studies, and that computational models can help to address some of the practical limitations of these approaches to record formation. A case study from arid Australia, examining the effects of episodic surface erosion on the visibility of the record, shows how simple, generative simulations, grounded in formational logic, can be used to compare different explanatory mechanisms and suggest tests of the archaeological record itself.


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