Public data mining plus domestic experimental study defined involvement of the old-yet-uncharacterized gene matrix-remodeling associated 7 (MXRA7) in physiopathology of the eye

Gene ◽  
2017 ◽  
Vol 632 ◽  
pp. 43-49 ◽  
Author(s):  
Changkai Jia ◽  
Feng Zhang ◽  
Ying Zhu ◽  
Xia Qi ◽  
Yiqiang Wang
2021 ◽  
Author(s):  
Scott A. Jarmusch ◽  
Justin J. J. van der Hooft ◽  
Pieter C. Dorrestein ◽  
Alan K. Jarmusch

This review covers the current and potential use of mass spectrometry-based metabolomics data mining in natural products. Public data, metadata, databases and data analysis tools are critical. The value and success of data mining rely on community participation.


2016 ◽  
Vol 12 (1) ◽  
pp. 11-30 ◽  
Author(s):  
Kay L. O’Halloran ◽  
Sabine Tan ◽  
Duc-Son Pham ◽  
John Bateman ◽  
Andrew Vande Moere

This article demonstrates how a digital environment offers new opportunities for transforming qualitative data into quantitative data in order to use data mining and information visualization for mixed methods research. The digital approach to mixed methods research is illustrated by a framework which combines qualitative methods of multimodal discourse analysis with quantitative methods of data mining and information visualization in a multilevel, contextual model that will result in an integrated, theoretically well-founded, and empirically evaluated technology for analyzing large data sets of multimodal texts. The framework is applicable to situations in which critical information needs to be extracted from geotagged public data: for example, in crisis informatics, where public reports of extreme events provide valuable data sources for disaster management.


2021 ◽  
Vol 12 ◽  
Author(s):  
Yupei Zhang ◽  
Yue Yun ◽  
Rui An ◽  
Jiaqi Cui ◽  
Huan Dai ◽  
...  

Student performance prediction (SPP) aims to evaluate the grade that a student will reach before enrolling in a course or taking an exam. This prediction problem is a kernel task toward personalized education and has attracted increasing attention in the field of artificial intelligence and educational data mining (EDM). This paper provides a systematic review of the SPP study from the perspective of machine learning and data mining. This review partitions SPP into five stages, i.e., data collection, problem formalization, model, prediction, and application. To have an intuition on these involved methods, we conducted experiments on a data set from our institute and a public data set. Our educational dataset composed of 1,325 students, and 832 courses was collected from the information system, which represents a typical higher education in China. With the experimental results, discussions on current shortcomings and interesting future works are finally summarized from data collections to practices. This work provides developments and challenges in the study task of SPP and facilitates the progress of personalized education.


Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 801 ◽  
Author(s):  
Carlos Peris-Torres ◽  
María del Carmen Plaza-Calonge ◽  
Raúl López-Domínguez ◽  
Silvia Domínguez-García ◽  
Antonio Barrientos-Durán ◽  
...  

Extracellular matrix remodeling within the tumor microenvironment has been recognized as a relevant dynamic framework during tumor growth. However, research on proteases that trigger this remodeling keeps revealing a wide range of actions including both pro- and anti-tumorigenic. The extracellular protease ADAMTS1 exemplifies this dual role. In this work, we first confirmed a positive correlation of ADAMTS1 with endothelial-like phenotype of human melanoma cells together with the finding of associated signatures, including key genes such as endothelial CDH5. Using a CRISPR-Cas9 approach, we observed that the inhibition of ADAMTS1 in an aggressive uveal melanoma model compromised its endothelial-like properties, and more importantly, caused a robust blockade on the progression of tumor xenografts. Although vasculature emerged affected in ADAMTS1-deficient tumors, the most relevant action implied the downregulation of endothelial CDH5 in tumor cells, in association with stemness markers. Indeed, melanoma sphere assays also revealed a deficient commitment to form spheres in the absence of ADAMTS1, directly correlating with stemness markers and, remarkably, also with CDH5. Finally, taking advantage of advanced bioinformatics tools and available public data of uveal melanomas, we disclosed new prognosis factors, including endothelial elements and ADAMTS proteases. Our findings support the key role of ADAMTS proteases for uveal melanoma development since earlier stages, modulating the complex crosstalk between extracellular matrix and the induction of stemness and endothelial-like features. To our knowledge, this is the first report that supports the development of therapeutic targets on the extracellular matrix to overcome uveal melanoma.


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