학술논문
Current and future directions in network biology
Document Type
Working Paper
Author
Zitnik, Marinka; Li, Michelle M.; Wells, Aydin; Glass, Kimberly; Gysi, Deisy Morselli; Krishnan, Arjun; Murali, T. M.; Radivojac, Predrag; Roy, Sushmita; Baudot, Anaïs; Bozdag, Serdar; Chen, Danny Z.; Cowen, Lenore; Devkota, Kapil; Gitter, Anthony; Gosline, Sara; Gu, Pengfei; Guzzi, Pietro H.; Huang, Heng; Jiang, Meng; Kesimoglu, Ziynet Nesibe; Koyuturk, Mehmet; Ma, Jian; Pico, Alexander R.; Pržulj, Nataša; Przytycka, Teresa M.; Raphael, Benjamin J.; Ritz, Anna; Sharan, Roded; Shen, Yang; Singh, Mona; Slonim, Donna K.; Tong, Hanghang; Yang, Xinan Holly; Yoon, Byung-Jun; Yu, Haiyuan; Milenković, Tijana
Source
Subject
Language
Abstract
Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field has been around for two decades, it remains nascent. It has witnessed rapid evolution, accompanied by emerging challenges. These challenges stem from various factors, notably the growing complexity and volume of data together with the increased diversity of data types describing different tiers of biological organization. We discuss prevailing research directions in network biology and highlight areas of inference and comparison of biological networks, multimodal data integration and heterogeneous networks, higher-order network analysis, machine learning on networks, and network-based personalized medicine. Following the overview of recent breakthroughs across these five areas, we offer a perspective on the future directions of network biology. Additionally, we offer insights into scientific communities, educational initiatives, and the importance of fostering diversity within the field. This paper establishes a roadmap for an immediate and long-term vision for network biology.
Comment: 52 pages, 6 figures, 1 table
Comment: 52 pages, 6 figures, 1 table