  Introduction: The extracellular matrix (ECM) is a networkof proteins and
carbohydrates that has a structural and bio-chemical function. The ECM plays an
important role in dif-ferentiation, migration and signaling. Several studies
havepredicted ECM proteins using machine learning algorithmssuch as Random
Forests, K-nearest neighbours and supportvector machines but is yet to be
explored using deep learn-ing. Method: DeepECMP was developed using several
previ-ously used ECM datasets, asymmetric undersampling andan ensemble of 11
feed-forward neural networks. Results: The performance of DeepECMP was 83.6%
bal-anced accuracy which outperformed several algorithms. Inaddition, the
pipeline of DeepECMP has been shown to behighly efficient. Conclusion: This
paper is the first to focus on utilizingdeep learning for ECM prediction.
Several limitations areovercome by DeepECMP such as computational
expense,availability to the public and usability outside of the humanspecies
