Enrico Glaab

According to our database, Enrico Glaab authored at least 19 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson's disease.

Cyril Brzenczek, Quentin Klopfenstein, Tom Hähnel, Holger Fröhlich, Enrico Glaab, Geeta Acharya, Gloria Aguayo, Myriam Alexandre, Muhammad Ali, Wim Ammerlann, Giuseppe Arena, Michele Bassis, Roxane Batutu, Katy Beaumont, Sibylle Béchet, Guy Berchem, Alexandre Bisdorff, Ibrahim Boussaad, David Bouvier, Lorieza Castillo, Gessica Contesotto, Nancy De Bremaeker, Brian Dewitt, Nico Diederich, Rene Dondelinger, Nancy E. Ramia, Angelo Ferrari, Katrin Frauenknecht, Joëlle Fritz, Carlos Gamio, Manon Gantenbein, Piotr Gawron, Laura Georges, Soumyabrata Ghosh, Marijus Giraitis, Martine Goergen, Elisa Gómez de Lope, Jérôme Graas, Mariella Graziano, Valentin Grouès, Anne Grünewald, Gaël Hammot, Anne-Marie Hanff, Linda Hansen, Michael Heneka, Estelle Henry, Margaux Henry, Sylvia Herbrink, Sascha Herzinger, Alexander Hundt, Nadine Jacoby, Sonja Jónsdóttir, Jochen Klucken, Olga Kofanova, Rejko Krüger, Pauline Lambert, Zied Landoulsi, Roseline Lentz, Ana Festas Lopes, Victoria Lorentz, Tainá M. Marques, Guilherme Marques, Patricia Martins Conde, Patrick May, Deborah Mcintyre, Chouaib Mediouni, Francoise Meisch, Alexia Mendibide, Myriam Menster, Maura Minelli, Michel Mittelbronn, Saïda Mtimet, Maeva Munsch, Romain Nati, Ulf Nehrbass, Sarah Nickels, Beatrice Nicolai, Jean-Paul Nicolay, Maria Fernanda Niño Uribe, Fozia Noor, Clarissa P. C. Gomes, Sinthuja Pachchek, Claire Pauly, Laure Pauly, Lukas Pavelka, Magali Perquin, Achilleas Pexaras, Armin Rauschenberger, Rajesh Rawal, Dheeraj Reddy Bobbili, Lucie Remark, Ilsé Richard, Olivia Roland, Kirsten Roomp, Eduardo Rosales, Stefano Sapienza, Venkata Satagopam, Sabine Schmitz, Reinhard Schneider, Jens Schwamborn, Raquel Severino, Amir Sharify, Ruxandra Soare, Ekaterina Soboleva, Kate Sokolowska, Maud Theresine, Hermann Thien, Elodie Thiry, Rebecca Ting Jiin Loo, Johanna Trouet, Olena Tsurkalenko, Michel Vaillant, Carlos Vega, Liliana Vilas Boas, Paul Wilmes, Evi Wollscheid-Lengeling, Gelani Zelimkhanov

npj Digit. Medicine, 2024

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease.

Elisa Gómez de Lope, Saurabh Deshpande, Ramón Viñas Torné, Pietro Liò, Enrico Glaab, Stéphane P. A. Bordas

CoRR, 2024

Bioinformatics approaches for studying molecular sex differences in complex diseases.

Rebecca Ting Jiin Loo, Mohamed Soudy, Francesco Nasta, Mirco Macchi, Enrico Glaab

Briefings Bioinform., 2024

2023

Penalized regression with multiple sources of prior effects.

Armin Rauschenberger, Zied Landoulsi, Mark A. van de Wiel, Enrico Glaab

Bioinform., December, 2023

2022

Ten quick tips for biomarker discovery and validation analyses using machine learning.

Ramón Díaz-Uriarte, Elisa Gómez de Lope, Rosalba Giugno, Holger Fröhlich, Petr V. Nazarov, Isabel A. Nepomuceno-Chamorro, Armin Rauschenberger, Enrico Glaab

PLoS Comput. Biol., 2022

2021

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge.

Solveig K. Sieberts, Jennifer Schaff, Marlena Duda, Bálint Á Pataki, Ming Sun, Phil Snyder, Jean-Francois Daneault, Federico Parisi, Gianluca Costante, Udi Rubin, Peter Banda, Yooree Chae, Elias Chaibub Neto, Earl Ray Dorsey, Zafer Aydin, Aipeng Chen, Laura L. Elo, Carlos Espino, Enrico Glaab, Ethan Goan, Fatemeh Noushin Golabchi, Yasin Görmez, Maria K. Jaakkola, Jitendra Jonnagaddala, Riku Klén, Dongmei Li, Christian McDaniel, Dimitri Perrin, Thanneer M. Perumal, Nastaran Mohammadian Rad, Erin Rainaldi, Stefano Sapienza, Patrick Schwab, Nikolai Shokhirev, Mikko S. Venäläinen, Gloria Vergara-Diaz, Yuqian Zhang, Avner G. S. Abrami, Aditya Adhikary, Carla Agurto, Sherry Bhalla, Halil Ibrahim Bilgin, Vittorio Caggiano, Jun Cheng, Eden Deng, Qiwei Gan, Rajan Girsa, Zhi Han, Stephen Heisig, Kun Huang, Samad Jahandideh, Wolfgang Kopp, Christoph F. Kurz, Gregor Lichtner, Raquel Norel, G. P. S. Raghava, Tavpritesh Sethi, Nicholas Shawen, Vaibhav Tripathi, Matthew Tsai, Tongxin Wang, Yi Wu, Jie Zhang, Xinyu Zhang, Yuanjia Wang, Yuanfang Guan, Daniela Brunner, Paolo Bonato, Lara M. Mangravite, Larsson Omberg

npj Digit. Medicine, 2021

Pharmacophore Model for SARS-CoV-2 3CLpro Small-Molecule Inhibitors and in Vitro Experimental Validation of Computationally Screened Inhibitors.

Enrico Glaab, Ganesh Babu Manoharan, Daniel Abankwa

J. Chem. Inf. Model., 2021

Predicting correlated outcomes from molecular data.

Armin Rauschenberger, Enrico Glaab

Bioinform., 2021

Predictive and interpretable models via the stacked elastic net.

Armin Rauschenberger, Enrico Glaab, Mark A. van de Wiel

Bioinform., 2021

2016

Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification.

Enrico Glaab

Briefings Bioinform., 2016

Building a virtual ligand screening pipeline using free software: a survey.

Enrico Glaab

Briefings Bioinform., 2016

2015

RepExplore: addressing technical replicate variance in proteomics and metabolomics data analysis.

Enrico Glaab, Reinhard Schneider

Bioinform., 2015

2012

PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data.

Enrico Glaab, Reinhard Schneider

Bioinform., 2012

EnrichNet: network-based gene set enrichment analysis.

Enrico Glaab, Anaïs Baudot, Natalio Krasnogor, Reinhard Schneider, Alfonso Valencia

Bioinform., 2012

2011

Analysing functional genomics data using novel ensemble, consensus and data fusion techniques.

Enrico Glaab

PhD thesis, 2011

2010

Extending pathways and processes using molecular interaction networks to analyse cancer genome data.

Enrico Glaab, Anaïs Baudot, Natalio Krasnogor, Alfonso Valencia

BMC Bioinform., 2010

TopoGSA: network topological gene set analysis.

Enrico Glaab, Anaïs Baudot, Natalio Krasnogor, Alfonso Valencia

Bioinform., 2010

Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples.

Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasnogor

Proceedings of the German Conference on Bioinformatics 2010, 2010

2009

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization.

Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasnogor

BMC Bioinform., 2009