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Yin Q, Wang Z, Xia C, Dehmer M, Emmert-Streib F, Jin Z. 2020. A novel epidemic model considering demographics and intercity commuting on complex dynamical networks. Applied Mathematics and Computation. 386. https://doi.org/10.1016/j.amc.2020.125517

Singh AK, Ahonen A, Ghabcheloo R, Mueller A. 2020. Introducing Multi-Convexity in Path Constrained Trajectory Optimization for Mobile Manipulators. In European Control Conference 2020, ECC 2020. IEEE. pp. 1178-1185.

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Ghorbani M, Dehmer M, Maimani H, Maddah S, Roozbayani M, Emmert-Streib F. 2020. The watching system as a generalization of identifying code. Applied Mathematics and Computation. 380. https://doi.org/10.1016/j.amc.2020.125302

Wan P, Tu J, Dehmer M, Zhang S, Emmert-Streib F. 2019. Graph entropy based on the number of spanning forests of c-cyclic graphs. Applied Mathematics and Computation. 363. https://doi.org/10.1016/j.amc.2019.124616

Dehmer M, Chen Z, Shi Y, Zhang Y, Tripathi S, Ghorbani M, Mowshowitz A, Emmert-Streib F. 2019. On efficient network similarity measures. Applied Mathematics and Computation. 362. https://doi.org/10.1016/j.amc.2019.06.035

Hella L, Kuusisto A, Meier A, Vollmer H. 2019. Satisfiability of modal inclusion logic: Lax and strict semantics. ACM TRANSACTIONS ON COMPUTATIONAL LOGIC. 21(1). https://doi.org/10.1145/3356043

Yang D, Qian Y, Cai D, Yan S, Kämäräinen J-K, Chen K. 2019. Visibility-Aware Part Coding for Vehicle Viewing Angle Estimation. In 9th International Conference on Information Science and Technology, ICIST 2019. IEEE. pp. 65-70. https://doi.org/10.1109/ICIST.2019.8836907

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Guzmán Adán A, Orelma H, Sommen F. 2019. Hypermonogenic solutions and plane waves of the Dirac operator in Rp×Rq. Applied Mathematics and Computation. 346:1-14. https://doi.org/10.1016/j.amc.2018.09.058

Kuang Y, Ma S, Ukkonen L, Virkki J, Björninen T. 2019. Circularly Polarized Textile Tag Antenna for Wearable Passive UHF RFID Systems. In 2018 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2018. IEEE. https://doi.org/10.23919/ACESS.2018.8669314

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Levämäki H, Tian L-Y, Vitos L, Ropo M. 2019. An automated algorithm for reliable equation of state fitting of magnetic systems. Computational Materials Science. 156:121-128. https://doi.org/10.1016/j.commatsci.2018.09.026

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Kartasalo K, Latonen L, Vihinen J, Visakorpi T, Nykter M, Ruusuvuori P. 2018. Comparative analysis of tissue reconstruction algorithms for 3D histology. Bioinformatics. 34(17):3013-3021. https://doi.org/10.1093/bioinformatics/bty210

Carabias Orti JJ, Nikunen J, Virtanen T, Vera-Candeas P. 2018. Multichannel Blind Sound Source Separation using Spatial Covariance Model with Level and Time Differences and Non-Negative Matrix Factorization. IEEE/ACM Transactions on Audio Speech and Language Processing. 26(9):1512-1527. https://doi.org/10.1109/TASLP.2018.2830105

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Dong G, Shen Y, He H, Virkki J, Hu S. 2017. Chipless graphene tag and dual-CP reader for Internet of Things. In 2017 International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2017. IEEE.

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Stupnikov A, Tripathi S, De Matos Simoes R, McArt D, Salto-Tellez M, Glazko G, Dehmer M, Emmert-Streib F. 2016. SamExploreR: Exploring reproducibility and robustness of RNA-seq results based on SAM files. Bioinformatics. 32(21):3345-3347. https://doi.org/10.1093/bioinformatics/btw475

Luukko PJJ, Helske J, Räsänen E. 2016. Introducing libeemd: a program package for performing the ensemble empirical mode decomposition. Computational Statistics. 31(2):545-557. https://doi.org/10.1007/s00180-015-0603-9

Häkkinen A, Ribeiro AS. 2016. Characterizing rate limiting steps in transcription from RNA production times in live cells. Bioinformatics. 32(9):1346-1352. https://doi.org/10.1093/bioinformatics/btv744

Dumitrescu B, Şicleru BC, Avram F. 2016. Modeling probability densities with sums of exponentials via polynomial approximation. Journal of Computational and Applied Mathematics. 292:513–525. https://doi.org/10.1016/j.cam.2015.07.032

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Ylinen A, Mäkinen J, Kouhia R. 2016. Two models for hydraulic cylinders in flexible multibody simulations. In Computational Methods for Solids and Fluids: Multiscale Analysis, Probability Aspects and Model Reduction. Springer. pp. 463-493. (Computational Methods in Applied Sciences). https://doi.org/10.1007/978-3-319-27996-1_17

Rodrigues PC, Monteiro A, Lourenço VM. 2015. A robust AMMI model for the analysis of genotype-by-environment data. Bioinformatics. 32(1):58-66. https://doi.org/10.1093/bioinformatics/btv533

Dehmer M, Emmert-Streib F, Shi Y. 2015. Graph distance measures based on topological indices revisited. Applied Mathematics and Computation. 266:623-633. https://doi.org/10.1016/j.amc.2015.05.072

Häkkinen A, Ribeiro AS. 2015. Estimation of GFP-tagged RNA numbers from temporal fluorescence intensity data. Bioinformatics. 31(1):69-75. https://doi.org/10.1093/bioinformatics/btu592

Karilainen T, Cramariuc O, Kuisma M, Tappura K, Hukka TI. 2015. Van der Waals interactions are critical in Car-Parrinello molecular dynamics simulations of porphyrin-fullerene dyads. Journal of Computational Chemistry. 36(9):612-621. https://doi.org/10.1002/jcc.23834

Chen Z, Dehmer M, Emmert-Streib F, Shi Y. 2014. Entropy bounds for dendrimers. Applied Mathematics and Computation. 242:462-472. https://doi.org/10.1016/j.amc.2014.05.105

Tripathi S, Dehmer M, Emmert-Streib F. 2014. NetBioV: An R package for visualizing large network data in biology and medicine. Bioinformatics. 30(19):2834-2836. https://doi.org/10.1093/bioinformatics/btu384

Rahmatallah Y, Emmert-Streib F, Glazko G. 2014. Gene Sets Net Correlations Analysis (GSNCA): A multivariate differential coexpression test for gene sets. Bioinformatics. 30(3):360-368. https://doi.org/10.1093/bioinformatics/btt687

Wang J, Ray AK. 2014. A full-potential linearized augmented plane wave study of the interaction of CO2 with α-Pu (020) surface nanolayers. Journal of Computational and Theoretical Nanoscience. 11(7):1710-1717. https://doi.org/10.1166/jctn.2014.3555

Enkavi G, Li J, Wen P, Thangapandian S, Moradi M, Jiang T, Han W, Tajkhorshid E. 2014. A microscopic view of the mechanisms of active transport across the cellular membrane. Annual Reports in Computational Chemistry. 10:77-125. https://doi.org/10.1016/B978-0-444-63378-1.00004-5

Airiskallio E, Nurmi E, Väyrynen IJ, Kokko K, Ropo M, Punkkinen MPJ, Johansson B, Vitos L. 2014. Magnetic origin of the chemical balance in alloyed Fe-Cr stainless steels: First-principles and Ising model study. Computational Materials Science. 92:135-140. https://doi.org/10.1016/j.commatsci.2014.05.036

Dehmer M, Grabner M, Mowshowitz A, Emmert-Streib F. 2013. An efficient heuristic approach to detecting graph isomorphism based on combinations of highly discriminating invariants. Advances in Computational Mathematics. 39(2):311-325. https://doi.org/10.1007/s10444-012-9281-0

Ma L, Wang J, Hao Y, Wang G. 2013. Density functional theory study of FePdn (n = 2-14) clusters and interactions with small molecules. Computational Materials Science. 68:166-173. https://doi.org/10.1016/j.commatsci.2012.10.014

Ma L, Ray AK. 2013. Growth behavior and magnetic properties of spherical uranium oxide nanoclusters. Journal of Computational and Theoretical Nanoscience. 10(2):334-340. https://doi.org/10.1166/jctn.2013.2701

Rahmatallah Y, Emmert-Streib F, Glazko G. 2012. Gene set analysis for self-contained tests: Complex null and specific alternative hypotheses. Bioinformatics. 28(23):3073-3080. https://doi.org/10.1093/bioinformatics/bts579

Emmert-Streib F. 2012. Universal construction mechanism for networks from one-dimensional symbol sequences. Applied Mathematics and Computation. 219(3):1020-1030. https://doi.org/10.1016/j.amc.2012.07.006

Emmert-Streib F. 2012. Evolutionary dynamics of the spatial Prisoner's Dilemma with self-inhibition. Applied Mathematics and Computation. 218(11):6482-6488. https://doi.org/10.1016/j.amc.2011.12.018

Uusitalo MA, Peltonen J, Ryhänen T. 2011. Machine learning: How it can help nanocomputing. Journal of Computational and Theoretical Nanoscience. 8(8):1347-1363. https://doi.org/10.1166/jctn.2011.1821

Yu G, Zhang B, Bova GS, Xu J, Shih IM, Wang Y. 2011. BACOM: In silico detection of genomic deletion types and correction of normal cell contamination in copy number data. Bioinformatics. 27(11):1473-1480. https://doi.org/10.1093/bioinformatics/btr183

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Altay G, Emmert-Streib F. 2010. Revealing differences in gene network inference algorithms on the network level by ensemble methods. Bioinformatics. 26(14):1738-1744. https://doi.org/10.1093/bioinformatics/btq259

Glazko GV, Emmert-Streib F. 2009. Unite and conquer: Univariate and multivariate approaches for finding differentially expressed gene sets. Bioinformatics. 25(18):2348-2354. https://doi.org/10.1093/bioinformatics/btp406

Dehmer M, Emmert-Streib F, Gesell T. 2008. A comparative analysis of multidimensional features of objects resembling sets of graphs. Applied Mathematics and Computation. 196(1):221-235. https://doi.org/10.1016/j.amc.2007.05.058

Dehmer M, Emmert-Streib F. 2007. Structural similarity of directed universal hierarchical graphs: A low computational complexity approach. Applied Mathematics and Computation. 194(1):7-20. https://doi.org/10.1016/j.amc.2007.04.006

Emmert-Streib F, Dehmer M. 2007. Information theoretic measures of UHG graphs with low computational complexity. Applied Mathematics and Computation. 190(2):1783-1794. https://doi.org/10.1016/j.amc.2007.02.095

Dehmer M, Emmert-Streib F. 2007. Comparing large graphs efficiently by margins of feature vectors. Applied Mathematics and Computation. 188(2):1699-1710. https://doi.org/10.1016/j.amc.2006.11.185

Emmert-Streib F, Dehmer M. 2007. Topological mappings between graphs, trees and generalized trees. Applied Mathematics and Computation. 186(2):1326-1333. https://doi.org/10.1016/j.amc.2006.07.162

Dehmer M, Emmert-Streib F, Kilian J. 2006. A similarity measure for graphs with low computational complexity. Applied Mathematics and Computation. 182(1):447-459. https://doi.org/10.1016/j.amc.2006.04.006

Emmert-Streib F. 2006. Algorithmic computation of knot polynomials of secondary structure elements of proteins. Journal of Computational Biology. 13(8):1503-1512. https://doi.org/10.1089/cmb.2006.13.1503

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