Tom Michoel - RankMe

30 papers A* 1C 1Journal 25Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Tesla-Rapture: A Lightweight Gesture Recognition System From mmWave Radar Sparse Point Clouds. IEEE Trans. Mob. Comput. Dariush Salami, Ramin Hasibi, Sameera Palipana, Petar Popovski, Tom Michoel, Stephan Sigg
2022	J	`jnl`	Causal inference in drug discovery and development. CoRR Tom Michoel, Jitao David Zhang
2022	J	`jnl`	rfPhen2Gen: A machine learning based association study of brain imaging phenotypes to genotypes. CoRR Muhammad Ammar Malik, Alexander Selvikvåg Lundervold, Tom Michoel
2021	J	`jnl`	A Graph Feature Auto-Encoder for the prediction of unobserved node features on biological networks. BMC Bioinform. Ramin Hasibi, Tom Michoel
2021	—	`conf`	High-Dimensional Multi-trait GWAS By Reverse Prediction of Genotypes Using Machine Learning Methods. CIBB Muhammad Ammar Malik, Adriaan-Alexander Ludl, Tom Michoel
2021	J	`jnl`	High-dimensional multi-trait GWAS by reverse prediction of genotypes. CoRR Muhammad Ammar Malik, Adriaan-Alexander Ludl, Tom Michoel
2021	J	`jnl`	Integrating Sensing and Communication in Cellular Networks via NR Sidelink. CoRR Dariush Salami, Ramin Hasibi, Stefano Savazzi, Tom Michoel, Stephan Sigg
2021	J	`jnl`	Tesla-Rapture: A Lightweight Gesture Recognition System from mmWave Radar Point Clouds. CoRR Dariush Salami, Ramin Hasibi, Sameera Palipana, Petar Popovski, Tom Michoel, Stephan Sigg
2020	J	`jnl`	Model-based clustering of multi-tissue gene expression data. Bioinform. Pau Erola, Johan Björkegren, Tom Michoel
2020	J	`jnl`	Predicting gene expression from network topology using graph neural networks. CoRR Ramin Hasibi, Tom Michoel
2020	J	`jnl`	Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders. CoRR Muhammad Ammar Malik, Tom Michoel
2018	A*	`conf`	Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net. NeurIPS Tom Michoel
2017	J	`jnl`	Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net. CoRR Tom Michoel
2017	J	`jnl`	Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data. PLoS Comput. Biol. Lingfei Wang, Tom Michoel
2016	J	`jnl`	Natural coordinate descent algorithm for L1-penalised regression in generalised linear models. Comput. Stat. Data Anal. Tom Michoel
2015	J	`jnl`	Integrative Multi-omics Module Network Inference with Lemon-Tree. PLoS Comput. Biol. Eric Bonnet, Laurence Calzone, Tom Michoel
2015	J	`jnl`	Multi-Species Network Inference Improves Gene Regulatory Network Reconstruction for Early Embryonic Development in J. Comput. Biol. Anagha Joshi, Yvonne Beck, Tom Michoel
2014	J	`jnl`	kruX: matrix-based non-parametric eQTL discovery. BMC Bioinform. Jianlong Qi, Hassan Asl, Johan Björkegren, Tom Michoel
2012	J	`jnl`	Alignment and integration of complex networks by hypergraph-based spectral clustering CoRR Tom Michoel, Bruno Nachtergaele
2012	J	`jnl`	Context-specific transcriptional regulatory network inference from global gene expression maps using double two-way Bioinform. Jianlong Qi, Tom Michoel
2012	J	`jnl`	MotifSuite: workflow for probabilistic motif detection and assessment. Bioinform. Marleen Claeys, Valerie Storms, Hong Sun, Tom Michoel, Kathleen Marchal
2011	—	`conf`	An integrative approach to infer regulation programs in a transcription regulatory module network. BCB Jianlong Qi, Tom Michoel, Gregory Butler
2011	—	`conf`	Applying Linear Models to Learn Regulation Programs in a Transcription Regulatory Module Network. EvoBio Jianlong Qi, Tom Michoel, Gregory Butler
2011	J	`jnl`	CyClus3D: a Cytoscape plugin for clustering network motifs in integrated networks. Bioinform. Pieter Audenaert, Thomas Van Parys, Florian Brondel, Mario Pickavet, Piet Demeester, Yves Van de Peer, Tom Michoel
2010	C	`conf`	A regression tree-based Gibbs sampler to learn the regulation programs in a transcription regulatory module network. CIBCB Jianlong Qi, Tom Michoel, Gregory Butler
2010	J	`jnl`	Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data. Bioinform. Eric Bonnet, Tom Michoel, Yves Van de Peer
2009	J	`jnl`	Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks. BMC Syst. Biol. Tom Michoel, Riet De Smet, Anagha Joshi, Yves Van de Peer, Kathleen Marchal
2009	J	`jnl`	Module networks revisited: computational assessment and prioritization of model predictions. Bioinform. Anagha Joshi, Riet De Smet, Kathleen Marchal, Yves Van de Peer, Tom Michoel
2008	J	`jnl`	Analysis of a Gibbs sampler method for model-based clustering of gene expression data. Bioinform. Anagha Joshi, Yves Van de Peer, Tom Michoel
2007	J	`jnl`	Validating module network learning algorithms using simulated data. BMC Bioinform. Tom Michoel, Steven Maere, Eric Bonnet, Anagha Joshi, Yvan Saeys, Tim Van den Bulcke, Koenraad Van Leemput, Piet van Remortel, Martin Kuiper, Kathleen Marchal, Yves Van de Peer