Luca Cappelletti

An Open-Source Knowledge Graph Ecosystem for the Life Sciences

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but...

KG-Hub -- Building and Exchanging Biological Knowledge Graphs

Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and...

GRAPE for Fast and Scalable Graph Processing and random walk-based Embedding

Graph Representation Learning (GRL) methods opened new avenues for addressing complex, real-world problems represented by graphs. However, many graphs used in these applications comprise millions...

Billion-scale Detection of Isomorphic Nodes

Bayesian Optimization Improves Tissue-Specific Prediction of Active Regulatory Regions with Deep Neural Networks

Degree-Normalization Improves Random-Walk-Based Embedding Accuracy in PPI Graphs

Semi-automatic Column Type Inference for CSV Table Understanding

A Web Tool for the Semantic Integration of Heterogeneous and Complex Spreadsheet Tables

KG-Microbe: A Reference Knowledge-Graph and Platform for Harmonized Microbial Information

On the Quality of Classification Models for Inferring ABAC Policies from Access Logs

Parallel Triangles and Squares Count for Multigraphs Using Vertex Covers