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Additional file 1 Supplementary Figures S1-S5 with each legend. Fig S1. Meta-Hi-C network benchmarking in mouse. Fig S2. Meta-Hi-C network benchmarking in human. Fig S3. TAD coexpression vs contact coexpression. Fig S4. TAD and boundary conservation across experiments. Fig. S5. Contact coexpression conservation at various coexpression thresholds.

Additional file 3 Review history.

Motivation: Clusters of hydrophobic residues are known to promote structured protein stability and drive protein aggregation. Recent work has shown that identifying contiguous hydrophobic residue clusters (termed "blobs") has proven useful in both intrinsically disordered protein (IDP) simulation and human genome studies. However, a graphical interface was unavailable., Results: Here, we present the blobulator: an interactive and intuitive web interface to detect intrinsic modularity in any protein sequence based on hydrophobicity. We demonstrate three use cases of the blobulator and show how identifying blobs with biologically relevant parameters provides useful information about a globular protein, two orthologous membrane proteins, and an IDP. Other potential applications are discussed, including: predicting protein segments with critical roles in tertiary interactions, providing a definition of local order and disorder with clear edges, and aiding in predicting protein features from sequence., Availability: The blobulator GUI can be found at www.blobulator.branniganlab.org, and the source code with pip installable command line tool can be found on GitHub at www.GitHub.com/BranniganLab/blobulator.