T. Kogej

发表

Thierry Kogej, Sorel Muresan, S. Muresan, 2005, Current drug discovery technologies.

Big pharma screening collections: more of the same or unique libraries? The AstraZeneca-Bayer Pharma AG case.

Thierry Kogej, Jörg Hüser, Niklas Blomberg, 2013, Drug discovery today.

Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?

Andreas Bender, Ola Engkvist, Thierry Kogej, 2017, Journal of chemical information and modeling.

Exploring in silico prediction of the unbound brain-to-plasma drug concentration ratio: model validation, renewal, and interpretation.

Jonna C. Stålring, L. Carlsson, O. Engkvist, 2015, Journal of pharmaceutical sciences.

HIGHLY POLAR CHROMOPHORES IN POLED POLYMER FILMS CHARACTERISED BY SECOND HARMONIC GENERATION

Thierry Kogej, David Beljonne, David Bloor, 1997 .

Structure–Second-Order Polarizability Relationship in Chromophores

A. Persoons, P. Dubois, J. Brédas, 1999 .

Development and design of the tertiary amino effect reaction for DNA-encoded library synthesis

G. Basarab, N. Selmi, R. Goodnow, 2016 .

Datasets and their influence on the development of computer assisted synthesis planning tools in the pharmaceutical domain† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c9sc04944d

J. Reymond, O. Engkvist, Amol Thakkar, 2019, Chemical science.

Designing a Combinatorial Library by Using Reagent Pharmacophore Fingerprint

N. Blomberg, O. Engkvist, U. Börjesson, 2009 .

Collaborative virtual screening to elaborate an imidazo[1,2-a]pyridine hit series for visceral leishmaniasis†

O. Engkvist, G. Pairaudeau, H. Nakai, 2020, RSC medicinal chemistry.

LibINVENT: Reaction-based Generative Scaffold Decoration for in Silico Library Design

O. Engkvist, E. Bjerrum, K. Papadopoulos, 2021, J. Chem. Inf. Model..

Secondary metabolites from cetrarioid lichens: Chemotaxonomy, biological activities and pharmaceutical potential.

R. Buonfiglio, S. Ómarsdóttir, T. Kogej, 2016, Phytomedicine : international journal of phytotherapy and phytopharmacology.

Dual NK1 Antagonists—Serotonin Reuptake Inhibitors as Potential Antidepressants. Part 2. SAR and Activity of Benzyloxyphenethyl Piperazine Derivatives.

R. Grimée, Y. Lamberty, T. Ryckmans, 2003 .

Design of organic molecules with large two-photon absorption cross sections.

W. Webb, J. Perry, M. Albota, 1998, Science.

Designing novel building blocks is an overlooked strategy to improve compound quality.

Matthew W D Perry, Thierry Kogej, Frederick W Goldberg, 2015, Drug discovery today.

Pyrazolone methylamino piperidine derivatives as novel CCR3 antagonists.

M. Gillard, P. Pasau, T. Kogej, 2007, Bioorganic & medicinal chemistry letters.

Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

Thierry Kogej, Marwin H. S. Segler, Mark P. Waller, 2017, ACS central science.

AI-assisted synthesis prediction.

Ola Engkvist, Hongming Chen, Samuel Genheden, 2019, Drug discovery today. Technologies.

Multifingerprint Based Similarity Searches for Targeted Class Compound Selection

Thierry Kogej, Sorel Muresan, Ola Engkvist, 2006, J. Chem. Inf. Model..

Approaches using AI in medicinal chemistry

Thierry Kogej, Eva Nittinger, Christian Tyrchan, 2022, Computational and Data-Driven Chemistry Using Artificial Intelligence.

Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research

Johan Karlsson, Thierry Kogej, Ola Engkvist, 2019, Front. Pharmacol..

Dual NK(1) antagonists--serotonin reuptake inhibitors as potential antidepressants. Part 2: SAR and activity of benzyloxyphenethyl piperazine derivatives.

R. Grimée, Y. Lamberty, T. Ryckmans, 2002, Bioorganic & medicinal chemistry letters.

Investigating Pharmacological Similarity by Charting Chemical Space

Thierry Kogej, Ola Engkvist, Péter L. Várkonyi, 2015, J. Chem. Inf. Model..

ChemGPS-NPWeb: chemical space navigation online

Thierry Kogej, Sorel Muresan, Johan Gottfries, 2009, J. Comput. Aided Mol. Des..

Tuning the two-photon absorption response of quadrupolar organic molecules

J. Perry, J. Brédas, S. Marder, 2002 .

Mechanisms for enhancement of two-photon absorption in donor–acceptor conjugated chromophores

Thierry Kogej, Seth R. Marder, David Beljonne, 1998 .

Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks pdf

Thierry Kogej, Christian Tyrchan, Marwin H. S. Segler, 2017, ArXiv.

Theoretical Design of Organic Chromophores with Large Two-Photon Absorption Cross-Sections

W. Webb, J. Perry, S. Hess, 2000 .

On the use of real-world datasets for reaction yield prediction

John E. Herr, N. Chawla, O. Wiest, 2021, Chemical Science.

Collaborative Virtual Screening Identifies a 2-Aryl-4-aminoquinazoline Series with Efficacy in an In Vivo Model of Trypanosoma cruzi Infection

O. Engkvist, G. Pairaudeau, David Shum, 2023, Journal of medicinal chemistry.

Physicochemical property profiles of marketed drugs, clinical candidates and bioactive compounds.

Thierry Kogej, Sorel Muresan, Ola Engkvist, 2009, Bioorganic & medicinal chemistry letters.

Cheminformatics in Drug Discovery, an Industrial Perspective

Ola Engkvist, Hongming Chen, Thierry Kogej, 2018, Molecular informatics.

Automated Recycling of Chemistry for Virtual Screening and Library Design

Thierry Kogej, Florian Raubacher, Mikko J. Vainio, 2012, J. Chem. Inf. Model..

Nonlinear optical properties of π-conjugated compounds incorporating a saturated spacer group

R. Silbey, J. Brédas, S. Marder, 1997 .

Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition

Julie Clark, Andreas Verras, Chris L. Waller, 2017, J. Chem. Inf. Model..

Novel functionalized oligo-vinylthiophene molecules with modulated second-order nonlinear optical response

A. Persoons, P. Dubois, J. Brédas, 2000 .

Making every SAR point count: the development of Chemistry Connect for the large-scale integration of structure and bioactivity data.

Thierry Kogej, Sorel Muresan, Christian Tyrchan, 2011, Drug discovery today.

Comparison of Molecular Fingerprint Methods on the Basis of Biological Profile Data

Thierry Kogej, Ola Engkvist, Christian Tyrchan, 2009, J. Chem. Inf. Model..

Prediction of the Chemical Context for Buchwald‐Hartwig Coupling Reactions

O. Engkvist, S. Genheden, S. Olsson, 2021, Molecular informatics.

SARConnect: A Tool to Interrogate the Connectivity Between Proteins, Chemical Structures and Activity Data

Sorel Muresan, Martin Johansson, Christian Tyrchan, 2012, Molecular informatics.

Scaffold Hopping by Fragment Replacement

Thierry Kogej, Jens Sadowski, Florian Raubacher, 2013, J. Chem. Inf. Model..

Compound Properties and their Influence on Drug Quality

Thierry Kogej, Ola Engkvist, Hongming Chen, 2015 .

Exploring in silico prediction of the unbound brain-to-plasma drug concentration ratio: model validation, renewal, and interpretation.

Jonna C. Stålring, L. Carlsson, O. Engkvist, 2015, Journal of pharmaceutical sciences.

Venn-Abers predictors for improved compound iterative screening in drug discovery

Thierry Kogej, Lars Carlsson, Ola Engkvist, 2018, COPA.