arXiv Open Access 2025

Bizard: A Community-Driven Platform for Accelerating and Enhancing Biomedical Data Visualization

Kexin Li Hu Zheng Kexin Huang Yinying Chai Yujie Peng +26 lainnya
Lihat Sumber

Abstrak

Biomedical research increasingly relies on heterogeneous, high-dimensional datasets, yet effective visualization remains hindered by fragmented code resources, steep programming barriers, and limited domain-specific guidance. Bizard is an open-source visualization code repository engineered to streamline data analysis in biomedical research. It aggregates a diverse array of executable visualization scripts, empowering researchers to select and tailor optimal graphical methods for their specific investigative demands. The platform features an intuitive interface equipped with sophisticated browsing and filtering capabilities, exhaustive tutorials, and interactive discussion forums that foster knowledge dissemination. Through its community-driven paradigm, Bizard promotes continual refinement and functional expansion, establishing itself as an essential resource for elevating biomedical data visualization and analytical standards. By harnessing Bizard's infrastructure, researchers can augment their visualization proficiency, propel methodological progress, and enhance interpretive rigor, ultimately accelerating precision medicine and personalized therapeutics. Bizard is freely accessible at https://openbiox.github.io/Bizard/.

Topik & Kata Kunci

Penulis (31)

K

Kexin Li

H

Hu Zheng

K

Kexin Huang

Y

Yinying Chai

Y

Yujie Peng

C

Chunyang Wang

X

Xuyang Yi

Z

Zilun Jin

H

Hong Yang

Y

Yun Peng

Y

Ying Shi

X

Xinhe Lu

J

Jiarui Bian

Y

Yirun Wang

R

Rongao Kou

D

Demin Gao

H

Hanbo Zhao

J

Juan Zhang

D

Dan Huang

K

Kaiyu Zhu

C

Chenxu Wu

Z

Zeruo Yang

Z

Zheng Kuang

M

Mo Liu

Z

Zhiwei Bao

Y

Yuzhong Peng

B

Benben Miao

J

Jianming Zeng

J

Jianfeng Li

P

Peng Luo

S

Shixiang Wang

Format Sitasi

Li, K., Zheng, H., Huang, K., Chai, Y., Peng, Y., Wang, C. et al. (2025). Bizard: A Community-Driven Platform for Accelerating and Enhancing Biomedical Data Visualization. https://arxiv.org/abs/2503.06845

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓