%% BioMed_Central_Bib_Style_v1.01

\begin{thebibliography}{52}
% BibTex style file: bmc-mathphys.bst (version 2.1), 2014-07-24
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\csname PreBibitemsHook\endcsname

%%% 1
\bibitem{chandrasekaran_solving_2019}
\begin{botherref}
\oauthor{\bsnm{Chandrasekaran}, \binits{A.}},
\oauthor{\bsnm{Kamal}, \binits{D.}},
\oauthor{\bsnm{Batra}, \binits{R.}},
\oauthor{\bsnm{Kim}, \binits{C.}},
\oauthor{\bsnm{Chen}, \binits{L.}},
\oauthor{\bsnm{Ramprasad}, \binits{R.}}:
Solving the electronic structure problem with machine learning.
npj Computational Materials
\textbf{5}(1).
doi:\doiurl{10.1038/s41524-019-0162-7}
\end{botherref}
\endbibitem

%%% 2
\bibitem{gomez-bombarelli_design_2016}
\begin{botherref}
\oauthor{\bsnm{Gómez-Bombarelli}, \binits{R.}},
\oauthor{\bsnm{Aguilera-Iparraguirre}, \binits{J.}},
\oauthor{\bsnm{Hirzel}, \binits{T.D.}},
\oauthor{\bsnm{Duvenaud}, \binits{D.}},
\oauthor{\bsnm{Maclaurin}, \binits{D.}},
\oauthor{\bsnm{Blood-Forsythe}, \binits{M.A.}},
\oauthor{\bsnm{Chae}, \binits{H.S.}},
\oauthor{\bsnm{Einzinger}, \binits{M.}},
\oauthor{\bsnm{Ha}, \binits{D.-G.}},
\oauthor{\bsnm{Wu}, \binits{T.}},
\oauthor{\bsnm{Markopoulos}, \binits{G.}},
\oauthor{\bsnm{Jeon}, \binits{S.}},
\oauthor{\bsnm{Kang}, \binits{H.}},
\oauthor{\bsnm{Miyazaki}, \binits{H.}},
\oauthor{\bsnm{Numata}, \binits{M.}},
\oauthor{\bsnm{Kim}, \binits{S.}},
\oauthor{\bsnm{Huang}, \binits{W.}},
\oauthor{\bsnm{Hong}, \binits{S.I.}},
\oauthor{\bsnm{Baldo}, \binits{M.}},
\oauthor{\bsnm{Adams}, \binits{R.P.}},
\oauthor{\bsnm{Aspuru-Guzik}, \binits{A.}}:
Design of efficient molecular organic light-emitting diodes by a
  high-throughput virtual screening and experimental approach.
Nature Materials
\textbf{15}(10),
1120--1127.
doi:\doiurl{10.1038/nmat4717}
\end{botherref}
\endbibitem

%%% 3
\bibitem{sahu_toward_2018}
\begin{botherref}
\oauthor{\bsnm{Sahu}, \binits{H.}},
\oauthor{\bsnm{Rao}, \binits{W.}},
\oauthor{\bsnm{Troisi}, \binits{A.}},
\oauthor{\bsnm{Ma}, \binits{H.}}:
Toward predicting efficiency of organic solar cells via machine learning and
  improved descriptors.
Advanced Energy Materials
\textbf{8}(24),
1801032.
doi:\doiurl{10.1002/aenm.201801032}
\end{botherref}
\endbibitem

%%% 4
\bibitem{choudhary_accelerated_2019}
\begin{botherref}
\oauthor{\bsnm{Choudhary}, \binits{K.}},
\oauthor{\bsnm{Bercx}, \binits{M.}},
\oauthor{\bsnm{Jiang}, \binits{J.}},
\oauthor{\bsnm{Pachter}, \binits{R.}},
\oauthor{\bsnm{Lamoen}, \binits{D.}},
\oauthor{\bsnm{Tavazza}, \binits{F.}}:
Accelerated discovery of efficient solar cell materials using quantum and
  machine-learning methods.
Chemistry of Materials
\textbf{31}(15),
5900--5908.
doi:\doiurl{10.1021/acs.chemmater.9b02166}
\end{botherref}
\endbibitem

%%% 5
\bibitem{sun_use_2019}
\begin{botherref}
\oauthor{\bsnm{Sun}, \binits{W.}},
\oauthor{\bsnm{Li}, \binits{M.}},
\oauthor{\bsnm{Li}, \binits{Y.}},
\oauthor{\bsnm{Wu}, \binits{Z.}},
\oauthor{\bsnm{Sun}, \binits{Y.}},
\oauthor{\bsnm{Lu}, \binits{S.}},
\oauthor{\bsnm{Xiao}, \binits{Z.}},
\oauthor{\bsnm{Zhao}, \binits{B.}},
\oauthor{\bsnm{Sun}, \binits{K.}}:
The use of deep learning to fast evaluate organic photovoltaic materials.
Advanced Theory and Simulations
\textbf{2}(1),
1800116.
doi:\doiurl{10.1002/adts.201800116}
\end{botherref}
\endbibitem

%%% 6
\bibitem{sun_machine_2019}
\begin{botherref}
\oauthor{\bsnm{Sun}, \binits{W.}},
\oauthor{\bsnm{Zheng}, \binits{Y.}},
\oauthor{\bsnm{Yang}, \binits{K.}},
\oauthor{\bsnm{Zhang}, \binits{Q.}},
\oauthor{\bsnm{Shah}, \binits{A.A.}},
\oauthor{\bsnm{Wu}, \binits{Z.}},
\oauthor{\bsnm{Sun}, \binits{Y.}},
\oauthor{\bsnm{Feng}, \binits{L.}},
\oauthor{\bsnm{Chen}, \binits{D.}},
\oauthor{\bsnm{Xiao}, \binits{Z.}},
\oauthor{\bsnm{Lu}, \binits{S.}},
\oauthor{\bsnm{Li}, \binits{Y.}},
\oauthor{\bsnm{Sun}, \binits{K.}}:
Machine learning–assisted molecular design and efficiency prediction for
  high-performance organic photovoltaic materials.
Science Advances
\textbf{5}(11),
4275.
doi:\doiurl{10.1126/sciadv.aay4275}
\end{botherref}
\endbibitem

%%% 7
\bibitem{padula_combining_2019}
\begin{botherref}
\oauthor{\bsnm{Padula}, \binits{D.}},
\oauthor{\bsnm{Simpson}, \binits{J.D.}},
\oauthor{\bsnm{Troisi}, \binits{A.}}:
Combining electronic and structural features in machine learning models to
  predict organic solar cells properties.
Materials Horizons
\textbf{6}(2),
343--349.
doi:\doiurl{10.1039/C8MH01135D}
\end{botherref}
\endbibitem

%%% 8
\bibitem{sumita_hunting_2018}
\begin{botherref}
\oauthor{\bsnm{Sumita}, \binits{M.}},
\oauthor{\bsnm{Yang}, \binits{X.}},
\oauthor{\bsnm{Ishihara}, \binits{S.}},
\oauthor{\bsnm{Tamura}, \binits{R.}},
\oauthor{\bsnm{Tsuda}, \binits{K.}}:
Hunting for organic molecules with artificial intelligence: Molecules optimized
  for desired excitation energies.
{ACS} Central Science
\textbf{4}(9),
1126--1133.
doi:\doiurl{10.1021/acscentsci.8b00213}
\end{botherref}
\endbibitem

%%% 9
\bibitem{hase_designing_2020}
\begin{barticle}
\bauthor{\bsnm{Häse}, \binits{F.}},
\bauthor{\bsnm{Roch}, \binits{L.M.}},
\bauthor{\bsnm{Friederich}, \binits{P.}},
\bauthor{\bsnm{Aspuru-Guzik}, \binits{A.}}:
\batitle{Designing and understanding light-harvesting devices with machine
  learning}.
\bjtitle{Nature Communications}
\bvolume{11}(\bissue{1}),
\bfpage{4587}
(\byear{2020}).
doi:\doiurl{10.1038/s41467-020-17995-8}.
\bcomment{Number: 1 Publisher: Nature Publishing Group}
\end{barticle}
\endbibitem

%%% 10
\bibitem{wang_simulation_2020}
\begin{botherref}
\oauthor{\bsnm{Wang}, \binits{H.}},
\oauthor{\bsnm{Ji}, \binits{Y.}},
\oauthor{\bsnm{Li}, \binits{Y.}}:
Simulation and design of energy materials accelerated by machine learning.
{WIREs} Computational Molecular Science
\textbf{10}(1),
1421.
doi:\doiurl{10.1002/wcms.1421}
\end{botherref}
\endbibitem

%%% 11
\bibitem{ramakrishnan_quantum_2014}
\begin{barticle}
\bauthor{\bsnm{Ramakrishnan}, \binits{R.}},
\bauthor{\bsnm{Dral}, \binits{P.O.}},
\bauthor{\bsnm{Rupp}, \binits{M.}},
\bauthor{\bparticle{von} \bsnm{Lilienfeld}, \binits{O.A.}}:
\batitle{Quantum chemistry structures and properties of 134 kilo molecules}.
\bjtitle{Scientific Data}
\bvolume{1},
\bfpage{140022}
(\byear{2014}).
doi:\doiurl{10.1038/sdata.2014.22}
\end{barticle}
\endbibitem

%%% 12
\bibitem{diversity}
\begin{botherref}
\oauthor{\bsnm{Glavatskikh}, \binits{M.}},
\oauthor{\bsnm{Leguy}, \binits{J.}},
\oauthor{\bsnm{Hunault}, \binits{G.}},
\oauthor{\bsnm{Cauchy}, \binits{T.}},
\oauthor{\bsnm{Da~Mota}, \binits{B.}}:
Dataset’s chemical diversity limits the generalizability of machine learning
  predictions.
Journal of Cheminformatics
\textbf{11}(1)
(2019).
doi:\doiurl{10.1186/s13321-019-0391-2}
\end{botherref}
\endbibitem

%%% 13
\bibitem{fink_virtual_2005}
\begin{barticle}
\bauthor{\bsnm{Fink}, \binits{T.}},
\bauthor{\bsnm{Bruggesser}, \binits{H.}},
\bauthor{\bsnm{Reymond}, \binits{J.-L.}}:
\batitle{Virtual {Exploration} of the {Small}-{Molecule} {Chemical} {Universe}
  below 160 {Daltons}}.
\bjtitle{Angewandte Chemie International Edition}
\bvolume{44}(\bissue{10}),
\bfpage{1504}--\blpage{1508}
(\byear{2005}).
doi:\doiurl{10.1002/anie.200462457}
\end{barticle}
\endbibitem

%%% 14
\bibitem{fink_virtual_2007}
\begin{barticle}
\bauthor{\bsnm{Fink}, \binits{T.}},
\bauthor{\bsnm{Reymond}, \binits{J.-L.}}:
\batitle{Virtual {Exploration} of the {Chemical} {Universe} up to 11 {Atoms} of
  {C}, {N}, {O}, {F}: {Assembly} of 26.4 {Million} {Structures} (110.9
  {Million} {Stereoisomers}) and {Analysis} for {New} {Ring} {Systems},
  {Stereochemistry}, {Physicochemical} {Properties}, {Compound} {Classes}, and
  {Drug} {Discovery}}.
\bjtitle{Journal of Chemical Information and Modeling}
\bvolume{47}(\bissue{2}),
\bfpage{342}--\blpage{353}
(\byear{2007}).
doi:\doiurl{10.1021/ci600423u}
\end{barticle}
\endbibitem

%%% 15
\bibitem{reymond_enumeration_2012}
\begin{barticle}
\bauthor{\bsnm{Reymond}, \binits{J.-L.}},
\bauthor{\bsnm{Ruddigkeit}, \binits{L.}},
\bauthor{\bsnm{Blum}, \binits{L.}},
\bauthor{\bsnm{Deursen}, \binits{R.v.}}:
\batitle{The enumeration of chemical space}.
\bjtitle{Wiley Interdisciplinary Reviews: Computational Molecular Science}
\bvolume{2}(\bissue{5}),
\bfpage{717}--\blpage{733}
(\byear{2012}).
doi:\doiurl{10.1002/wcms.1104}
\end{barticle}
\endbibitem

%%% 16
\bibitem{nakata_pubchemqc_2017}
\begin{barticle}
\bauthor{\bsnm{Nakata}, \binits{M.}},
\bauthor{\bsnm{Shimazaki}, \binits{T.}}:
\batitle{{PubChemQC} {Project}: {A} {Large}-{Scale} {First}-{Principles}
  {Electronic} {Structure} {Database} for {Data}-{Driven} {Chemistry}}.
\bjtitle{Journal of Chemical Information and Modeling}
\bvolume{57}(\bissue{6}),
\bfpage{1300}--\blpage{1308}
(\byear{2017}).
doi:\doiurl{10.1021/acs.jcim.7b00083}.
Accessed 2017-07-07
\end{barticle}
\endbibitem

%%% 17
\bibitem{panapitiya_predicting_2021}
\begin{botherref}
\oauthor{\bsnm{Panapitiya}, \binits{G.}},
\oauthor{\bsnm{Girard}, \binits{M.}},
\oauthor{\bsnm{Hollas}, \binits{A.}},
\oauthor{\bsnm{Murugesan}, \binits{V.}},
\oauthor{\bsnm{Wang}, \binits{W.}},
\oauthor{\bsnm{Saldanha}, \binits{E.}}:
Predicting {Aqueous} {Solubility} of {Organic} {Molecules} {Using} {Deep}
  {Learning} {Models} with {Varied} {Molecular} {Representations}.
arXiv:2105.12638 [cond-mat]
(2021).
arXiv: 2105.12638
\end{botherref}
\endbibitem

%%% 18
\bibitem{vazquez-salazar_impact_2021}
\begin{botherref}
\oauthor{\bsnm{Vazquez-Salazar}, \binits{L.I.}},
\oauthor{\bsnm{Boittier}, \binits{E.}},
\oauthor{\bsnm{Unke}, \binits{O.T.}},
\oauthor{\bsnm{Meuwly}, \binits{M.}}:
Impact of the characteristics of quantum chemical databases on machine learning
  predictions of tautomerization energies.
arXiv:2104.06099 [physics]
(2021).
arXiv: 2104.06099
\end{botherref}
\endbibitem

%%% 19
\bibitem{evomol}
\begin{barticle}
\bauthor{\bsnm{Leguy}, \binits{J.}},
\bauthor{\bsnm{Cauchy}, \binits{T.}},
\bauthor{\bsnm{Glavatskikh}, \binits{M.}},
\bauthor{\bsnm{Duval}, \binits{B.}},
\bauthor{\bsnm{Da~Mota}, \binits{B.}}:
\batitle{{EvoMol}: a flexible and interpretable evolutionary algorithm for
  unbiased de novo molecular generation}.
\bjtitle{Journal of Cheminformatics}
\bvolume{12}(\bissue{1}),
\bfpage{55}
(\byear{2020}).
doi:\doiurl{10.1186/s13321-020-00458-z}
\end{barticle}
\endbibitem

%%% 20
\bibitem{guacamol}
\begin{barticle}
\bauthor{\bsnm{Brown}, \binits{N.}},
\bauthor{\bsnm{Fiscato}, \binits{M.}},
\bauthor{\bsnm{Segler}, \binits{M.H.S.}},
\bauthor{\bsnm{Vaucher}, \binits{A.C.}}:
\batitle{{GuacaMol}: {Benchmarking} {Models} for de {Novo} {Molecular}
  {Design}}.
\bjtitle{Journal of Chemical Information and Modeling}
\bvolume{59}(\bissue{3}),
\bfpage{1096}--\blpage{1108}
(\byear{2019}).
doi:\doiurl{10.1021/acs.jcim.8b00839}
\end{barticle}
\endbibitem

%%% 21
\bibitem{MOSES}
\begin{botherref}
\oauthor{\bsnm{Polykovskiy}, \binits{D.}},
\oauthor{\bsnm{Zhebrak}, \binits{A.}},
\oauthor{\bsnm{Sanchez-Lengeling}, \binits{B.}},
\oauthor{\bsnm{Golovanov}, \binits{S.}},
\oauthor{\bsnm{Tatanov}, \binits{O.}},
\oauthor{\bsnm{Belyaev}, \binits{S.}},
\oauthor{\bsnm{Kurbanov}, \binits{R.}},
\oauthor{\bsnm{Artamonov}, \binits{A.}},
\oauthor{\bsnm{Aladinskiy}, \binits{V.}},
\oauthor{\bsnm{Veselov}, \binits{M.}},
\oauthor{\bsnm{Kadurin}, \binits{A.}},
\oauthor{\bsnm{Johansson}, \binits{S.}},
\oauthor{\bsnm{Chen}, \binits{H.}},
\oauthor{\bsnm{Nikolenko}, \binits{S.}},
\oauthor{\bsnm{Aspuru-Guzik}, \binits{A.}},
\oauthor{\bsnm{Zhavoronkov}, \binits{A.}}:
Molecular {Sets} ({MOSES}): {A} {Benchmarking} {Platform} for {Molecular}
  {Generation} {Models}.
arXiv:1811.12823 [cs, stat]
(2020)
\end{botherref}
\endbibitem

%%% 22
\bibitem{benhenda_diversitynet}
\begin{botherref}
\oauthor{\bsnm{Benhenda}, \binits{M.}},
\oauthor{\bsnm{Bjerrum}, \binits{E.J.}},
\oauthor{\bsnm{yi}, \binits{h.}},
\oauthor{\bsnm{zaveri}, \binits{c.}}:
{DiversityNet}: a collaborative benchmark for generative {AI} models in
  chemistry.
Technical report,
Authorea, Inc.
doi:\doiurl{10.22541/au.155751672.29626289}
\end{botherref}
\endbibitem

%%% 23
\bibitem{KL}
\begin{barticle}
\bauthor{\bsnm{Kullback}, \binits{S.}},
\bauthor{\bsnm{Leibler}, \binits{R.A.}}:
\batitle{On information and sufficiency}.
\bjtitle{The Annals of Mathematical Statistics}
\bvolume{22}(\bissue{1}),
\bfpage{79}--\blpage{86}
(\byear{1951})
\end{barticle}
\endbibitem

%%% 24
\bibitem{frechet1957distance}
\begin{barticle}
\bauthor{\bsnm{Fr{\'e}chet}, \binits{M.}}:
\batitle{Sur la distance de deux lois de probabilit{\'e}}.
\bjtitle{Comptes rendus hebdomadaires des séances de l'Académie des sciences}
\bvolume{244}(\bissue{6}),
\bfpage{689}--\blpage{692}
(\byear{1957})
\end{barticle}
\endbibitem

%%% 25
\bibitem{BRICS}
\begin{barticle}
\bauthor{\bsnm{Degen}, \binits{J.}},
\bauthor{\bsnm{Wegscheid-Gerlach}, \binits{C.}},
\bauthor{\bsnm{Zaliani}, \binits{A.}},
\bauthor{\bsnm{Rarey}, \binits{M.}}:
\batitle{On the {Art} of {Compiling} and {Using} '{Drug}-{Like}' {Chemical}
  {Fragment} {Spaces}}.
\bjtitle{ChemMedChem}
\bvolume{3}(\bissue{10}),
\bfpage{1503}--\blpage{1507}
(\byear{2008}).
doi:\doiurl{10.1002/cmdc.200800178}
\end{barticle}
\endbibitem

%%% 26
\bibitem{scaffolds}
\begin{barticle}
\bauthor{\bsnm{Bemis}, \binits{G.W.}},
\bauthor{\bsnm{Murcko}, \binits{M.A.}}:
\batitle{The {Properties} of {Known} {Drugs}. 1. {Molecular} {Frameworks}}.
\bjtitle{Journal of Medicinal Chemistry}
\bvolume{39}(\bissue{15}),
\bfpage{2887}--\blpage{2893}
(\byear{1996}).
doi:\doiurl{10.1021/jm9602928}
\end{barticle}
\endbibitem

%%% 27
\bibitem{FCD}
\begin{barticle}
\bauthor{\bsnm{Preuer}, \binits{K.}},
\bauthor{\bsnm{Renz}, \binits{P.}},
\bauthor{\bsnm{Unterthiner}, \binits{T.}},
\bauthor{\bsnm{Hochreiter}, \binits{S.}},
\bauthor{\bsnm{Klambauer}, \binits{G.}}:
\batitle{Fréchet {ChemNet} {Distance}: {A} {Metric} for {Generative} {Models}
  for {Molecules} in {Drug} {Discovery}}.
\bjtitle{Journal of Chemical Information and Modeling}
\bvolume{58}(\bissue{9}),
\bfpage{1736}--\blpage{1741}
(\byear{2018}).
doi:\doiurl{10.1021/acs.jcim.8b00234}
\end{barticle}
\endbibitem

%%% 28
\bibitem{Jaccard}
\begin{barticle}
\bauthor{\bsnm{Jaccard}, \binits{P.}}:
\batitle{Distribution de la flore alpine dans le bassin des dranses et dans
  quelques régions voisines.}
\bjtitle{Bulletin de la Societe Vaudoise des Sciences Naturelles}
\bvolume{37},
\bfpage{241}--\blpage{72}
(\byear{1901}).
doi:\doiurl{10.5169/seals-266440}
\end{barticle}
\endbibitem

%%% 29
\bibitem{ECFP}
\begin{barticle}
\bauthor{\bsnm{Rogers}, \binits{D.}},
\bauthor{\bsnm{Hahn}, \binits{M.}}:
\batitle{Extended-{Connectivity} {Fingerprints}}.
\bjtitle{Journal of Chemical Information and Modeling}
\bvolume{50}(\bissue{5}),
\bfpage{742}--\blpage{754}
(\byear{2010}).
doi:\doiurl{10.1021/ci100050t}.
\bcomment{Publisher: American Chemical Society}
\end{barticle}
\endbibitem

%%% 30
\bibitem{ORGAN}
\begin{botherref}
\oauthor{\bsnm{Guimaraes}, \binits{G.L.}},
\oauthor{\bsnm{Sanchez-Lengeling}, \binits{B.}},
\oauthor{\bsnm{Outeiral}, \binits{C.}},
\oauthor{\bsnm{Farias}, \binits{P.L.C.}},
\oauthor{\bsnm{Aspuru-Guzik}, \binits{A.}}:
Objective-{Reinforced} {Generative} {Adversarial} {Networks} ({ORGAN}) for
  {Sequence} {Generation} {Models}
(2017).
\url{https://arxiv.org/abs/1705.10843}
\end{botherref}
\endbibitem

%%% 31
\bibitem{nigam_augmenting}
\begin{botherref}
\oauthor{\bsnm{Nigam}, \binits{A.}},
\oauthor{\bsnm{Friederich}, \binits{P.}},
\oauthor{\bsnm{Krenn}, \binits{M.}},
\oauthor{\bsnm{Aspuru-Guzik}, \binits{A.}}:
Augmenting {Genetic} {Algorithms} with {Deep} {Neural} {Networks} for
  {Exploring} the {Chemical} {Space}.
arXiv:1909.11655 [physics]
(2020)
\end{botherref}
\endbibitem

%%% 32
\bibitem{lipkus_structural_2008}
\begin{barticle}
\bauthor{\bsnm{Lipkus}, \binits{A.H.}},
\bauthor{\bsnm{Yuan}, \binits{Q.}},
\bauthor{\bsnm{Lucas}, \binits{K.A.}},
\bauthor{\bsnm{Funk}, \binits{S.A.}},
\bauthor{\bsnm{Bartelt}, \binits{W.F.}},
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</refgrp>
} % end of \BMCxmlcomment
