CAVEman: Standardized anatomical context for biomedical data mapping

Turinsky, Andrei L.; Fanea, E.; Trinh, Quang; Wat, Stephen; Hallgrímsson, Benedikt; Dong, Xiaoli; Shu, Xueling; Stromer, Julie N.; Edwards, Carol A.; Grosenick, Brenda; Yajima, Masumi; Sensen, Christoph Wilhelm

doi:10.1002/ase.3

Cited by 14 publications

(8 citation statements)

References 30 publications

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“…Among these is the BTO, a valuable tool for localizing enzymes in tissues and cell cultures. The CAVEman human anatomy is based on the Terminologia Anatomica and is the international standard on human anatomic terminology (12). SCOPe and CATH cover the structural classification of enzyme proteins (13,14).…”

Section: Retrieving Enzyme Information On the Brenda Websitementioning

confidence: 99%

BRENDA in 2017: new perspectives and new tools in BRENDA

Placzek¹,

Schomburg²,

Chang³

et al. 2016

Nucleic Acids Res

255

208

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The BRENDA enzyme database (www.brenda-enzymes.org) has developed into the main enzyme and enzyme-ligand information system in its 30 years of existence. The information is manually extracted from primary literature and extended by text mining procedures, integration of external data and prediction algorithms. Approximately 3 million data from 83 000 enzymes and 137 000 literature references constitute the manually annotated core. Text mining procedures extend these data with information on occurrence, enzyme-disease relationships and kinetic data. Prediction algorithms contribute locations and genome annotations. External data and links complete the data with sequences and 3D structures. A total of 206 000 enzyme ligands provide functional and structural data. BRENDA offers a complex query tool engine allowing the users an efficient access to the data via different search methods and explorers. The new design of the BRENDA entry page and the enzyme summary pages improves the user access and the performance. New interactive and intuitive BRENDA pathway maps give an overview on biochemical processes and facilitate the visualization of enzyme, ligand and organism information in the biochemical context. SCOPe and CATH, databases for protein structure classification, are included. New online and video tutorials provide online training for the users. BRENDA is freely available for academic users.

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Section: Retrieving Enzyme Information On the Brenda Websitementioning

confidence: 99%

BRENDA in 2017: new perspectives and new tools in BRENDA

Placzek¹,

Schomburg²,

Chang³

et al. 2016

Nucleic Acids Res

255

208

View full text Add to dashboard Cite

show abstract

“…Such digital models of the human body have been used extensively in anatomy education (Nguyen and Wilson,2009; Nowinski et al,2009; Petersson et al,2009), and the enthusiasm for using them is fueled by the rapidly developing digital technology that allows ever more realistic representation of the human body in the digital world. Not only do these digital models of the human body have the potential to eventually replace human cadavers in the dissection room, which require many resources for procurement, preparation, storage, and the actual teaching using them (Older,2004), they can even serve as a common platform for the integration of many different branches of knowledge, such as gene express, pharmacokinetics, and metabolic activity (Turinsky et al,2008).…”

Section: Introductionmentioning

confidence: 99%

An analysis of the educational value of low‐fidelity anatomy models as external representations

Chan¹,

Cheng²

2011

Anatomical Sciences Ed

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Although high-fidelity digital models of human anatomy based on actual cross-sectional images of the human body have been developed, reports on the use of physical models in anatomy teaching continue to appear. This article aims to examine the common features shared by these physical models and analyze their educational value based on the literature on cognition, learning, and external representations. A literature search on these physical models in three popular anatomy journals published over a 10-year period from 2001 to 2010 found that all of them have low fidelity: they oftentimes do not closely resemble the regions of the human body they are representing. They include only a small number of the structures that exist in these regions of the human body and do not accurately represent the shape and surface details of these structures. However, these models strongly correspond to the human body in the spatial relationship of the represented structures, which is crucial to achieving their educational purpose of teaching three-dimensional comprehension and anatomical reasoning. The educational value of these models includes acting as memory aids, reducing cognitive overload, facilitating problem solving, and arousing students' enthusiasm and participation. Because these models often lack a close resemblance to the human body, their use in anatomy teaching should always be accompanied by adequate explanations to the students to establish the correspondence between the models and the parts of the human body they are representing.

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“…Multiple windows and screens are supported to maximize the usable space. This feature also provides support for more advanced display configurations, such as two-projector stereoscopic 3D setups or CAVEs [21]. …”

Section: Methodsmentioning

confidence: 99%

Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of Multidimensional Data

Malek

Sensen

2018

International Journal of Biomedical Imaging

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Objective We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data. Methods A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes. Results GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations. Conclusion Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization. Significance This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.

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CAVEman: Standardized anatomical context for biomedical data mapping

Cited by 14 publications

References 30 publications

BRENDA in 2017: new perspectives and new tools in BRENDA

BRENDA in 2017: new perspectives and new tools in BRENDA

An analysis of the educational value of low‐fidelity anatomy models as external representations

Instant Feedback Rapid Prototyping for GPU-Accelerated Computation, Manipulation, and Visualization of Multidimensional Data

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