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pro vyhledávání: '"Apke, Alexander"'
Here we present a holistic approach for data exploration on dense knowledge graphs as a novel approach with a proof-of-concept in biomedical research. Knowledge graphs are increasingly becoming a vital factor in knowledge mining and discovery as they
Externí odkaz:
http://arxiv.org/abs/1912.06194
Autor:
Apke, Alexander, Schrader, Rainer
Publikováno v:
In Discrete Applied Mathematics 15 July 2021 297:142-150
Publikováno v:
Studies in Big Data ISBN: 9783031084102
Cham : Springer International Publishing, Studies in Big Data 112, 415-437 (2022). doi:10.1007/978-3-031-08411-9_15
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Cham : Springer International Publishing, Studies in Big Data 112, 415-437 (2022). doi:10.1007/978-3-031-08411-9_15
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
The collection and understanding of biological sequences once founded bioinformatics as a scientific field, and is still the most common reception even outside the scientific community. In this chapter we introduce principles of sequence analysis, st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::718591308b0e75caa87643a8bbfc3b77
https://doi.org/10.1007/978-3-031-08411-9_15
https://doi.org/10.1007/978-3-031-08411-9_15
Publikováno v:
Studies in Big Data ISBN: 9783031084102
Cham : Springer International Publishing, Studies in Big Data 112, 21-54 (2022). doi:10.1007/978-3-031-08411-9_2
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Cham : Springer International Publishing, Studies in Big Data 112, 21-54 (2022). doi:10.1007/978-3-031-08411-9_2
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
This chapter is a principal introduction to the Java programming language, treating the setup of an adequate environment, basics and the integration of external libraries. Beyond, it provides information of using collaborative tools like Git. This qu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f6cb3594ede13225fb4e289b119306a
https://doi.org/10.1007/978-3-031-08411-9_2
https://doi.org/10.1007/978-3-031-08411-9_2
Publikováno v:
Studies in Big Data ISBN: 9783031084102
Cham : Springer, Studies in Big Data 112, 327-359 (2022). doi:10.1007/978-3-031-08411-9
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Cham : Springer, Studies in Big Data 112, 327-359 (2022). doi:10.1007/978-3-031-08411-9
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Network structures play an important role in life sciences and data representation. For example, they are used within biological and social networks, protein interaction networks. In this chapter, we introduce the analysis of graph structures with Ja
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd9549810f229402e3fafd711555e9fe
https://doi.org/10.1007/978-3-031-08411-9_12
https://doi.org/10.1007/978-3-031-08411-9_12
Publikováno v:
Studies in Big Data ISBN: 9783031084102
Cham : Springer International Publishing, Studies in Big Data 112, 397-413 (2022). doi:10.1007/978-3-031-08411-9_14
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Cham : Springer International Publishing, Studies in Big Data 112, 397-413 (2022). doi:10.1007/978-3-031-08411-9_14
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Image processing and manipulation is deeply related to the life sciences. The flood of new imaging devices, capable of higher resolutions and better technologies lead to an increasing number of digital images for medical biological diagnostics. Thoug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65462e452a2a74da5f428ec44aa1dcfc
https://doi.org/10.1007/978-3-031-08411-9_14
https://doi.org/10.1007/978-3-031-08411-9_14
Publikováno v:
Studies in Big Data ISBN: 9783031084102
Cham : Springer International Publishing, Studies in Big Data 112, 79-98 (2022). doi:10.1007/978-3-031-08411-9_4
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
Cham : Springer International Publishing, Studies in Big Data 112, 79-98 (2022). doi:10.1007/978-3-031-08411-9_4
[Ebook] Computational Life Sciences : Data Engineering and Data Mining for Life Sciences / Dörpinghaus, Jens ; Weil, Vera ; Schaaf, Sebastian ; Apke, Alexander 1st ed. 2022, Cham : Springer International Publishing, 2022
In this chapter, we have a closer look at algorithms and the challenges that lie in designing “good” algorithms. We show how a real world problem can be modeled in a way that an algorithm can understand and solve it. Further, we introduce the Big
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1731b1571d589badcd3ffbe50ebdc848
https://doi.org/10.1007/978-3-031-08411-9_4
https://doi.org/10.1007/978-3-031-08411-9_4
Here we present a holistic approach for data exploration on dense knowledge graphs as a novel approach with a proof-of-concept in biomedical research. Knowledge graphs are increasingly becoming a vital factor in knowledge mining and discovery as they
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d14db65f0e1befb898d6a55d29dfde0
http://arxiv.org/abs/1912.06194
http://arxiv.org/abs/1912.06194