pyRDF2Vec: A Python Implementation and Extension of RDF2Vec

1 code implementation • 4 May 2022 • Gilles Vandewiele, Bram Steenwinckel, Terencio Agozzino, Femke Ongenae

This paper introduces pyRDF2Vec, a Python software package that reimplements the well-known RDF2Vec algorithm along with several of its extensions.

Deep learning models for predicting RNA degradation via dual crowdsourcing

1 code implementation • 14 Oct 2021 • Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins, Do Soon Kim, Bojan Tunguz, Walter Reade, Maggie Demkin, Jonathan Romano, Roger Wellington-Oguri, John J. Nicol, Jiayang Gao, Kazuki Onodera, Kazuki Fujikawa, Hanfei Mao, Gilles Vandewiele, Michele Tinti, Bram Steenwinckel, Takuya Ito, Taiga Noumi, Shujun He, Keiichiro Ishi, Youhan Lee, Fatih Öztürk, Anthony Chiu, Emin Öztürk, Karim Amer, Mohamed Fares, Eterna Participants, Rhiju Das

Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504-1588 nucleotides) with improved accuracy compared to previously published models.

Data Augmentation

MAGIC: Mining an Augmented Graph using INK, starting from a CSV

1 code implementation • SemTab@ISWC 2021 • Bram Steenwinckel, Filip De Turck, Femke Ongenae

A large portion of structured data does not yet reap the benefits of the Semantic Web.

Cell Entity Annotation Column Type Annotation +1

Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs

1 code implementation • 9 Sep 2020 • Gilles Vandewiele, Bram Steenwinckel, Pieter Bonte, Michael Weyns, Heiko Paulheim, Petar Ristoski, Filip De Turck, Femke Ongenae

As KGs are symbolic constructs, specialized techniques have to be applied in order to make them compatible with data mining techniques.

Knowledge Graphs Language Modelling +1

Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge Graph

1 code implementation • International Workshop on Semantics-Powered Data Mining and Analytics 2019 • Gilles Vandewiele, Bram Steenwinckel, Femke Ongenae, Filip De Turck

Deep-learning based techniques are increasingly being used for different machine learning tasks on knowledge graphs.

Knowledge Graphs Node Classification