Protein complexes play a crucial role in cellular biological processes. Identifying these complexes is essential for understanding cellular functions and biological mechanisms. Graph clustering ...

ABSTRACT: This work describes a data integration model using the Statistical Matching methodology (hot deck distance) to integrate two surveys conducted by ISTAT (EU-SILC) and the Bank of Italy ...

We propose a hybrid methodology to evaluate the alignment between structural communities inferred from interaction networks and the linguistic coherence of users' textual production in online social ...

In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...

Co-clustering algorithms and models represent a robust framework for the simultaneous partitioning of the rows and columns in a data matrix. This dual clustering approach, often termed block ...

Many modern clustering methods scale well to a large number of data items, N, but not to a large number of clusters, K. This paper introduces PERCH, a new non-greedy algorithm for online hierarchical ...

Baseline predicted RNFL thickness derived from optic disc photographs can provide primary open-angle glaucoma risk information. An artificial intelligence (AI) deep learning model is capable of using ...

A project at Rice University has developed a new machine learning (ML) algorithm intended to improve the identification of biomarkers in optical spectra. As reported in ACS Nano, the algorithm could ...