التفاصيل البيبلوغرافية
| العنوان: |
Network Modeling in Biology: Statistical Methods for Gene and Brain Networks |
| المؤلفون: |
Wang, YX Rachel, Li, Lexin, Li, Jingyi Jessica, Huang, Haiyan |
| المصدر: |
Statistical Science, vol 36, iss 1 |
| بيانات النشر: |
eScholarship, University of California |
| سنة النشر: |
2021 |
| المجموعة: |
University of California: eScholarship |
| مصطلحات موضوعية: |
Bioengineering, Genetics, Neurosciences, Networking and Information Technology R&D (NITRD), 1.4 Methodologies and measurements, 2.5 Research design and methodologies (aetiology), Aetiology, Underpinning research, Gene regulatory networks, brain connectivity networks, network reconstruction, network inference, Statistics, Statistics & Probability |
| جغرافية الموضوع: |
89 - 108 |
| الوصف: |
The rise of network data in many different domains has offered researchers new insight into the problem of modeling complex systems and propelled the development of numerous innovative statistical methodologies and computational tools. In this paper, we primarily focus on two types of biological networks, gene networks and brain networks, where statistical network modeling has found both fruitful and challenging applications. Unlike other network examples such as social networks where network edges can be directly observed, both gene and brain networks require careful estimation of edges using covariates as a first step. We provide a discussion on existing statistical and computational methods for edge esitimation and subsequent statistical inference problems in these two types of biological networks. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
application/pdf |
| اللغة: |
unknown |
| العلاقة: |
qt1vj3r20c; https://escholarship.org/uc/item/1vj3r20cTest |
| الإتاحة: |
https://escholarship.org/uc/item/1vj3r20cTest |
| حقوق: |
public |
| رقم الانضمام: |
edsbas.46E36183 |
| قاعدة البيانات: |
BASE |
