The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

M Krallinger, M Vazquez, F Leitner, D Salgado… - BMC …, 2011 - Springer
Background Determining usefulness of biomedical text mining systems requires realistic
task definition and data selection criteria without artificial constraints, measuring …

Distance closures on complex networks

T Simas, LM Rocha - Network Science, 2015 - cambridge.org
To expand the toolbox available to network science, we study the isomorphism between
distance and Fuzzy (proximity or strength) graphs. Distinct transitive closures in Fuzzy …

Extraction of pharmacokinetic evidence of drug–drug interactions from the literature

A Kolchinsky, A Lourenço, HY Wu, L Li, LM Rocha - PloS one, 2015 - journals.plos.org
Drug-drug interaction (DDI) is a major cause of morbidity and mortality and a subject of
intense scientific interest. Biomedical literature mining can aid DDI research by extracting …

myAURA: Personalized health library for epilepsy management via knowledge graph sparsification and visualization

RB Correia, JC Rozum, L Cross, J Felag… - arXiv preprint arXiv …, 2024 - arxiv.org
Objective: We report the development of the patient-centered myAURA application and suite
of methods designed to aid epilepsy patients, caregivers, and researchers in making …

Measuring climate change on Twitter using Google's algorithm: Perception and events

AA Hamed, AA Ayer, EM Clark, EA Irons… - International Journal of …, 2015 - emerald.com
Purpose–The purpose of this paper is to test the hypothesis of whether more complex and
emergent hashtags can be sufficient pointers to climate change events. Human-induced …

Evaluation of linear classifiers on articles containing pharmacokinetic evidence of drug-drug interactions

A Kolchinsky, A Lourenço, L Li, LM Rocha - Biocomputing 2013, 2013 - World Scientific
Background. Drug-drug interaction (DDI) is a major cause of morbidity and mortality. DDI
research includes the study of different aspects of drug interactions, from in vitro …

Defect Severity Identification for a Catenary System Based on Deep Semantic Learning

J Wang, S Gao, L Yu, D Zhang, L Kou - Sensors, 2022 - mdpi.com
A variety of Chinese textual operational text data has been recorded during the operation
and maintenance of the high-speed railway catenary system. Such defect text records can …

Classification of research papers on radio frequency electromagnetic field (RF-EMF) using graph neural networks (GNN)

Y Jang, K Won, H Choi, SY Shin - Applied Sciences, 2023 - mdpi.com
This study compares the performance of graph convolutional neural network (GCN) models
with conventional natural language processing (NLP) models for classifying scientific …

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions

S Agarwal, F Liu, H Yu - BMC bioinformatics, 2011 - Springer
Background Protein-protein interaction (PPI) is an important biomedical phenomenon.
Automatically detecting PPI-relevant articles and identifying methods that are used to study …

Hybrid methods of bibliographic coupling and text similarity measurement for biomedical paper recommendation

H Guo, Z Shen, J Zeng, N Hong - MEDINFO 2021: One World …, 2022 - ebooks.iospress.nl
The amount of available scientific literature is increasing, and studies have proposed
various methods for evaluating document-document similarity in order to cluster or classify …