Author Archives: root

News coverage of our publication: High-Resolution Directed Human Connectomes and the Consensus Connectome Dynamics

Television report, broadcasted on May 4, 2019, in “Multiverzum”

Online articles:

News coverage of our publication: MetaHMM: A Webserver for Identifying Novel Genes with Specified Functions in Metagenomic Samples

Television report, broadcasted on November 3, 2018, in Novum TV “Hello Tomorrow”:

 

Online articles:

News coverage of our publication: SECLAF: A Webserver and Deep Neural Network Design Tool for Hierarchical Biological Sequence Classification:

Television report, broadcasted on April 3, 2018, in the magazine “Tudomány minden napra”:

News coverage of our publication: The Robustness and the Doubly-Preferential Attachment Simulation of the Consensus Connectome Dynamics of the Human Brain (in Hungarian):

Television report, broadcasted on December 8, 2017 on the first channel of the Hungarian Television, in the “Minden Tudás” magazine:

News coverage of our publication Comparative Connectomics

News coverage of our publication Comparative Connectomics (in Hungarian):

News coverage of our publication: Identifying Combinatorial Biomarkers by Association Rule Mining in the CAMD Alzheimer’s Database

Radio report, broadcasted on August 29, 2017 in the “Szigma” magazine of Inforadio:

Media reflections to our publication: Brain Size Bias Compensated Graph-Theoretical Parameters are Also Better in Women’s Structural Connectome

Television report, broadcasted on June 9, 2017 on the first channel of the Hungarian Television, in the “Minden Tudás” magazine:

Near Perfect Protein Multi-Label Classification with Deep Neural Networks

Our new paper “Near Perfect Protein Multi-Label Classification with Deep Neural Networks” was published on arxiv.org on 30 Mar 2017.

Artificial neural networks (ANNs) have gained a well-deserved popularity among machine learning tools upon their recent successful applications in image- and sound processing and classification problems. Here we present two new ANNs with multi-label classification ability, showing impressive accuracy when classifying protein sequences into 698 UniProt families (AUC=99.99%) and 983 Gene Ontology classes (AUC=99.45%).

See the article here: https://arxiv.org/abs/1703.10663

 

News coverage of our publication The “Giant Virus Finder” Discovers an Abundance of Giant Viruses in the Antarctic Dry Valleys

A 25-minute television report and a talk, first aired on June 3, 2017 on “Mindenki Akadémiája” on the Hungarian Television, on this result: