With a combination of new data sources and mixed methods including bibliometrics, machine learning and network analysis, this study puts forward a new framework of categorizing different interdisciplinary collaboration patterns from a discipline-contribution perspective. Based on 20,542 research articles published on PLoS series of journals in 2018, 14,744 articles with interdisciplinary collaborations (ICAs) are recognized. By establishing six indicators that measure the variety, similarity and balance of authors’ disciplines and their contribution roles, ICAs are divided into four categories after the agglomerative hierarchical clustering. With a fine-grained analysis of the structural and correlation characteristics of authors’ disciplines and contribution in different clusters, four interdisciplinary collaboration patterns of sheep flock, bee colony, intercropping and rainforest are found. Our results may contribute to developing new methodologies and theories of interdisciplinary collaboration, and enrich the understanding of interdisciplinary collaboration as well as relevant policies.