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Jan Jensen
PeerJ Editor, Author & Reviewer
2,925 Points

Contributions by role

Author 1,890
Preprint Author 560
Reviewer 140
Editor 335
Preprint Feedback 15
Answers 50
Comment 1

Contributions by subject area

Theoretical and Computational Chemistry
Photochemistry
Physical Chemistry (other)
Biophysics
Computational Biology
Biochemistry
Computational Science
Bioengineering
Biotechnology
Bioinformatics
Mathematical Biology
Science and Medical Education
Biophysical Chemistry
Pharmacology
Catalysis
Crystallography
Physical Organic Chemistry

By Q&A topic

Biochemistry
Biotechnology
Computational-biology
Computational-science
Biophysics

Jan H Jensen

PeerJ Editor, Author & Reviewer

Summary

Jan H. Jensen obtained his PhD in theoretical chemistry in 1995 from Iowa State University working with Mark Gordon, where he continued as a postdoc until he joined the faculty at the University of Iowa in 1997. In 2006 he moved to the University of Copenhagen, where he is now professor of bio-computational chemistry.

Prof. Jensen is the Editor-in-Chief of PeerJ Physical Chemistry.

Biophysical Chemistry Theoretical & Computational Chemistry

Editorial Board Member

PeerJ Physical Chemistry

Past or current institution affiliations

University of Copenhagen

Work details

Professor of Chemistry

University of Copenhagen
Department of Chemistry

Websites

  • Google Scholar
  • GitHub
  • Blog

PeerJ Contributions

  • Articles 16
  • Preprints 11
  • Edited 3
  • Reviewed 2
  • Feedback 3
  • Questions 1
  • Answers 5
January 6, 2025
Beyond predefined ligand libraries: a genetic algorithm approach for de novo discovery of catalysts for the Suzuki coupling reactions
Julius Seumer, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.34
December 5, 2023
Genetic algorithm-based re-optimization of the Schrock catalyst for dinitrogen fixation
Magnus Strandgaard, Julius Seumer, Bardi Benediktsson, Arghya Bhowmik, Tejs Vegge, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.30
March 16, 2022
Fast and automated identification of reactions with low barriers using meta-MD simulations
Maria H. Rasmussen, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.22
May 17, 2021
Using a genetic algorithm to find molecules with good docking scores
Casper Steinmann, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.18
February 10, 2021
High throughput virtual screening of 230 billion molecular solar heat battery candidates
Mads Koerstz, Anders S. Christensen, Kurt V. Mikkelsen, Mogens Brøndsted Nielsen, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.16
September 29, 2020
Fast and automatic estimation of transition state structures using tight binding quantum chemical calculations
Maria H. Rasmussen, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.15
July 31, 2020
Chemical space exploration: how genetic algorithms find the needle in the haystack
Emilie S. Henault, Maria H. Rasmussen, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.11
August 11, 2016
Prediction of pKa values using the PM6 semiempirical method
Jimmy C. Kromann, Frej Larsen, Hadeel Moustafa, Jan H. Jensen
https://doi.org/10.7717/peerj.2335 PubMed 27602298
May 3, 2016
Towards a barrier height benchmark set for biologically relevant systems
Jimmy C. Kromann, Anders S. Christensen, Qiang Cui, Jan H. Jensen
https://doi.org/10.7717/peerj.1994 PubMed 27168993
October 20, 2015
ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins
Anders S. Larsen, Lars A. Bratholm, Anders S. Christensen, Maher Channir, Jan H. Jensen
https://doi.org/10.7717/peerj.1344 PubMed 26623185
March 24, 2015
Bayesian inference of protein structure from chemical shift data
Lars A. Bratholm, Anders S. Christensen, Thomas Hamelryck, Jan H. Jensen
https://doi.org/10.7717/peerj.861 PubMed 25825683
June 19, 2014
A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+
Jimmy C. Kromann, Anders S. Christensen, Casper Steinmann, Martin Korth, Jan H. Jensen
https://doi.org/10.7717/peerj.449 PubMed 25024918
March 4, 2014
FragBuilder: an efficient Python library to setup quantum chemistry calculations on peptides models
Anders S. Christensen, Thomas Hamelryck, Jan H. Jensen
https://doi.org/10.7717/peerj.277 PubMed 24688855
October 31, 2013
Predicting pKa for proteins using COSMO-RS
Martin Peter Andersson, Jan Halborg Jensen, Susan Louise Svane Stipp
https://doi.org/10.7717/peerj.198 PubMed 24244915
August 29, 2013
In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB
Martin R. Hediger, Luca De Vico, Julie B. Rannes, Christian Jäckel, Werner Besenmatter, Allan Svendsen, Jan H. Jensen
https://doi.org/10.7717/peerj.145 PubMed 24010022
July 23, 2013
A computational method for the systematic screening of reaction barriers in enzymes: searching for Bacillus circulans xylanase mutants with greater activity towards a synthetic substrate
Martin R. Hediger, Casper Steinmann, Luca De Vico, Jan H. Jensen
https://doi.org/10.7717/peerj.111 PubMed 23904990
September 21, 2018 - Version: 1
Searching for the origin of life using a computational search engine
Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.27233v1
January 3, 2017 - Version: 1
Which method is more accurate? or errors have error bars
Jan H Jensen
https://doi.org/10.7287/peerj.preprints.2693v1
December 5, 2016 - Version: 2
Prediction of pKa values for drug-like molecules using semiempirical quantum chemical methods
Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.2564v2
September 27, 2016 - Version: 1
Protein structure refinement using a quantum mechanics-based chemical shielding predictor
Lars A. Bratholm, Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.2476v1
May 25, 2016 - Version: 1
Prediction of pKa values using the PM6 semiempirical method
Jimmy C. Kromann, Frej Larsen, Hadeel Moustafa, Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.2075v1
February 20, 2016 - Version: 2
Towards a barrier height benchmark set for biologically relevant systems
Jimmy C Kromann, Anders S Christensen, Qiang Cui, Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.1741v2
August 24, 2015 - Version: 2
ProCS15: A DFT-based chemical shift predictor for backbone and Cβ atoms in proteins
Anders S Larsen, Lars A Bratholm, Anders S Christensen, Maher Jan Channir, Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.1308v2
July 26, 2015 - Version: 1
My flipped classroom: what I did and how I did it
Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.1262v1
December 12, 2014 - Version: 1
Bayesian inference of protein structure from chemical shift data
Lars A Bratholm, Anders Steen Christensen, Thomas Hamelryck, Jan H Jensen
https://doi.org/10.7287/peerj.preprints.692v1
April 4, 2014 - Version: 1
A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+
Jimmy Charnley Kromann, Anders Christensen, Casper Steinmann, Martin Korth, Jan H. Jensen
https://doi.org/10.7287/peerj.preprints.353v1
February 6, 2014 - Version: 3
FragBuilder: An efficient Python library to setup quantum chemistry calculations on peptide models
Anders Steen Christensen, Thomas Hamelryck, Jan H Jensen
https://doi.org/10.7287/peerj.preprints.169v3

Academic Editor on

May 20, 2020
Benchmarking quantum mechanical methods for calculating reaction energies of reactions catalyzed by enzymes
Jitnapa Sirirak, Narin Lawan, Marc W. Van der Kamp, Jeremy N. Harvey, Adrian J. Mulholland
https://doi.org/10.7717/peerj-pchem.8
December 2, 2019
Spectrometric and computational studies of the binding of HIV-1 integrase inhibitors to viral DNA extremities
Léa El Khoury, Krystel El Hage, Jean-Philip Piquemal, Serge Fermandjian, Richard G. Maroun, Nohad Gresh, Zeina Hobaika
https://doi.org/10.7717/peerj-pchem.6
October 15, 2019
Outline of an experimental design aimed to detect protein A mirror image in solution
Osvaldo A. Martin, Yury Vorobjev, Harold A. Scheraga, Jorge A. Vila
https://doi.org/10.7717/peerj-pchem.2

Signed reviews submitted for articles published in PeerJ Note that some articles may not have the review itself made public unless authors have made them open as well.

October 15, 2019
Effects of number of parallel runs and frequency of bias-strength replacement in generalized ensemble molecular dynamics simulations
Takuya Shimato, Kota Kasahara, Junichi Higo, Takuya Takahashi
https://doi.org/10.7717/peerj-pchem.4
May 31, 2016
An explicit-solvent conformation search method using open software
Kari Gaalswyk, Christopher N. Rowley
https://doi.org/10.7717/peerj.2088 PubMed 27280078

Provided feedback on

1 vote
26 Mar 2015

Mechanistic pathways of mercury removal from the organomercurial lyase active site

Some quick comments 1.The charge and spin state of each model should be defined. 2. Constraining CA atoms is pretty standard in such studies, but I haven’t seen CB atoms constr...

01 Jun 2016

Prediction of pKa values using the PM6 semiempirical method

This preprint was submitted to PeerJ for peer review June 1, 2016

06 Jan 2017

Prediction of pKa values for drug-like molecules using semiempirical quantum chemical methods

This document is the unedited Author's version of a Submitted Work that was subsequently accepted for publication in Journal of Physical Chemistry A, copyright © American Chemical...

1 Question

0
PLoS ONE discipline and APC
about A survey of authors publishing in four megajournals

5 Answers

1
accepted Is ab initio data the best target?
1
Arbitrary Barrier cutoff
0
Supporting Information
0
Difference in barrier compared to Hediger 2012 PlosOne
0
accepted Is the method compatible with the simultaneous use of $QUANPOL in Gamess US?