Experimental design based 3-D QSAR analysis of steroid-protein interactions: Application to human CBG complexes. - Ulf Norinder (J. Comput. Aided Mol. Des., 1990)

3-D QSAR analysis of steroid/protein interactions: The use of difference maps. - Ulf Norinder (J. Comput. Aided Mol. Des., 1991)

A PLS QSAR analysis using 3D generated aromatic descriptors of principal property type: Application to some dopamine D2 benzamide antagonists. - Ulf Norinder (J. Comput. Aided Mol. Des., 1993)

Descriptors for amino acids using MolSurf parametrization. - Ulf Norinder; Peter Svensson (J. Comput. Chem., 1998)

Refinement of Catalyst hypotheses using simplex optimisation. - Ulf Norinder (J. Comput. Aided Mol. Des., 2000)

Prediction of Polar Surface Area and Drug Transport Processes Using Simple Parameters and PLS Statistics. - Thomas Österberg; Ulf Norinder (J. Chem. Inf. Comput. Sci., 2000)

Support vector machine models in drug design: applications to drug transport processes and QSAR using simplex optimisations and variable selection. - Ulf Norinder (Neurocomputing, 2003)

Molecular Descriptors Influencing Melting Point and Their Role in Classification of Solid Drugs. - Christel A. S. Bergström; Ulf Norinder; Kristina Luthman; Per Artursson (J. Chem. Inf. Comput. Sci., 2003)

Global and Local Computational Models for Aqueous Solubility Prediction of Drug-Like Molecules. - Christel A. S. Bergström; Carola M. Wassvik; Ulf Norinder; Kristina Luthman; Per Artursson (J. Chem. Inf. Model., 2004)

Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes. - Cecilia Sönströd; Ulf Johansson; Ulf Norinder; Henrik Boström (ICMLA, 2008)

Pre-Processing Structured Data for Standard Machine Learning Algorithms by Supervised Graph Propositionalization - A Case Study with Medicinal Chemistry Datasets. - Thashmee Karunaratne; Henrik Boström; Ulf Norinder (ICMLA, 2010)

Pin-pointing concept descriptions. - Cecilia Sönströd; Ulf Johansson; Henrik Boström; Ulf Norinder (SMC, 2010)

Evaluation of Quantitative Structure-Activity Relationship Modeling Strategies: Local and Global Models. - Ernst Ahlberg Helgee; Lars Carlsson; Scott Boyer; Ulf Norinder (J. Chem. Inf. Model., 2010)

Application of Conformal Prediction in QSAR. - Martin Eklund; Ulf Norinder; Scott Boyer; Lars Carlsson (AIAI (2), 2012)

A Pragmatic Approach Using First-Principle Methods to Address Site of Metabolism with Implications for Reactive Metabolite Formation. - Ya-Wen Hsiao; Carl Petersson; Mats Svensson; Ulf Norinder (J. Chem. Inf. Model., 2012)

Introducing Uncertainty in Predictive Modeling - Friend or Foe? - Ulf Norinder; Henrik Boström (J. Chem. Inf. Model., 2012)

Comparative analysis of the use of chemoinformatics-based and substructure-based descriptors for quantitative structure-activity relationship (QSAR) modeling. - Thashmee Karunaratne; Henrik Boström; Ulf Norinder (Intell. Data Anal., 2013)

QSAR with experimental and predictive distributions: an information theoretic approach for assessing model quality. - David J. Wood; Lars Carlsson; Martin Eklund; Ulf Norinder; Jonna C. Stålring (J. Comput. Aided Mol. Des., 2013)

Beyond the Scope of Free-Wilson Analysis: Building Interpretable QSAR Models with Machine Learning Algorithms. - Hongming Chen 001; Lars Carlsson; Mats Eriksson; Péter L. Várkonyi; Ulf Norinder; Ingemar Nilsson (J. Chem. Inf. Model., 2013)

Aggregated Conformal Prediction. - Lars Carlsson; Martin Eklund; Ulf Norinder (AIAI (Workshops), 2014)

Choosing Feature Selection and Learning Algorithms in QSAR. - Martin Eklund; Ulf Norinder; Scott Boyer; Lars Carlsson (J. Chem. Inf. Model., 2014)

Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination. - Ulf Norinder; Lars Carlsson; Scott Boyer; Martin Eklund (J. Chem. Inf. Model., 2014)

Conformal Prediction in Spark: Large-Scale Machine Learning with Confidence. - Marco Capuccini; Lars Carlsson; Ulf Norinder; Ola Spjuth (BDC, 2015)

The application of conformal prediction to the drug discovery process. - Martin Eklund; Ulf Norinder; Scott Boyer; Lars Carlsson (Ann. Math. Artif. Intell., 2015)

Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery. - Ernst Ahlberg; Susanne Winiwarter; Henrik Boström; Henrik Linusson; Tuve Löfström; Ulf Norinder; Ulf Johansson; Ola Engkvist; Oscar Hammar; Claus Bendtsen; Lars Carlsson (COPA, 2017)

On the Calibration of Aggregated Conformal Predictors. - Henrik Linusson; Ulf Norinder; Henrik Boström; Ulf Johansson; Tuve Löfström (COPA, 2017)

Maximizing Gain in HTS Screening Using Conformal Prediction. - Ulf Norinder; Fredrik Svensson; Avid M. Afzal; Andreas Bender 002 (COPA, 2017)

Improving Screening Efficiency through Iterative Screening Using Docking and Conformal Prediction. - Fredrik Svensson; Ulf Norinder; Andreas Bender 002 (J. Chem. Inf. Model., 2017)

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets. - Jiangming Sun; Lars Carlsson; Ernst Ahlberg; Ulf Norinder; Ola Engkvist; Hongming Chen 001 (J. Chem. Inf. Model., 2017)

Evaluating parameters for ligand-based modeling with random forest on sparse data sets. - Alexander Kensert; Jonathan Alvarsson; Ulf Norinder; Ola Spjuth (J. Cheminformatics, 2018)

Maximizing gain in high-throughput screening using conformal prediction. - Fredrik Svensson; Avid M. Afzal; Ulf Norinder; Andreas Bender 002 (J. Cheminformatics, 2018)

Conformal Regression for Quantitative Structure-Activity Relationship Modeling - Quantifying Prediction Uncertainty. - Fredrik Svensson; Natália Aniceto; Ulf Norinder; Isidro Cortes-Ciriano; Ola Spjuth; Lars Carlsson; Andreas Bender 002 (J. Chem. Inf. Model., 2018)

Multitask Modeling with Confidence Using Matrix Factorization and Conformal Prediction. - Ulf Norinder; Fredrik Svensson (J. Chem. Inf. Model., 2019)

LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets. - Jin Zhang; Daniel Mucs; Ulf Norinder; Fredrik Svensson (J. Chem. Inf. Model., 2019)

Using Predicted Bioactivity Profiles to Improve Predictive Modeling. - Ulf Norinder; Ola Spjuth; Fredrik Svensson (J. Chem. Inf. Model., 2020)

Correction to "Using Predicted Bioactivity Profiles to Improve Predictive Modeling". - Ulf Norinder; Ola Spjuth; Fredrik Svensson (J. Chem. Inf. Model., 2020)

Assessing the calibration in toxicological in vitro models with conformal prediction. - Andrea Morger; Fredrik Svensson; Staffan Arvidsson McShane; Niharika Gauraha; Ulf Norinder; Ola Spjuth; Andrea Volkamer (J. Cheminformatics, 2021)

Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning. - Ulf Norinder; Ola Spjuth; Fredrik Svensson (J. Cheminformatics, 2021)

ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities. - Marina Garcia de Lomana; Andrea Morger; Ulf Norinder; Roland Buesen; Robert Landsiedel; Andrea Volkamer; Johannes Kirchmair; Miriam Mathea (J. Chem. Inf. Model., 2021)

Deep Learning-Based Conformal Prediction of Toxicity. - Jin Zhang; Ulf Norinder; Fredrik Svensson (J. Chem. Inf. Model., 2021)

Identifying Novel Inhibitors for Hepatic Organic Anion Transporting Polypeptides by Machine Learning-Based Virtual Screening. - Alzbeta Türková; Brandon J. Bongers; Ulf Norinder; Orsolya Ungvári; Virág Székely; Andrey Tarnovskiy; Gergely Szakács; Csilla Özvegy-Laczka; Gerard J. P. van Westen; Barbara Zdrazil (J. Chem. Inf. Model., 2022)

Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells. - Olivier J. M. Béquignon; Jose C. Gómez-Tamayo; Eelke B. Lenselink; Steven Wink; Steven Hiemstra; Chi Chung Lam; Domenico Gadaleta; Alessandra Roncaglioni; Ulf Norinder; Bob van de Water; Manuel Pastor; Gerard J. P. van Westen (J. Chem. Inf. Model., 2023)

CPSign: conformal prediction for cheminformatics modeling. - Staffan Arvidsson McShane; Ulf Norinder; Jonathan Alvarsson; Ernst Ahlberg; Lars Carlsson; Ola Spjuth (J. Cheminformatics, 2024)

Rapid traversal of vast chemical space using machine learning-guided docking screens. - Andreas Luttens; Israel Cabeza de Vaca; Leonard Sparring; José M. Brea; Antón Leandro Martínez; Nour Aldin Kahlous; Dmytro S. Radchenko; Yurii S. Moroz; María Isabel Loza; Ulf Norinder; Jens Carlsson (Nat. Comput. Sci., 2025)