Papers at Google Scholar PubMed
97 journal articles in 63 different journals
97, Ivan Randelovic, Kinga Nyíri, Gergely Koppány, Marcel Baranyi, József Tóvári, Attila Kigyós, József Timár, Beáta G. Vértessy, Vince Grolmusz: Gluing GAP to RAS Mutants: A New Approach to an Old Problem in Cancer Drug Development, International Journal of Molecular Sciences Vol. 25 No. 5 2572; (2024) https://doi.org/10.3390/ijms25052572 [impact factor 5.6; Q1, D1]
96, András Telek, Zsófia Molnár, Kristóf Takács, Bálint Varga, Vince Grolmusz, Gábor Tasnádi, Beáta G. Vértessy: Discovery and biocatalytic characterization of opine dehydrogenases by metagenome mining, Applied Microbiology and Biotechnology 108:0 (2024)
https://doi.org/10.1007/s00253-023-12871-z [ impact factor 5.0; Q1}
95, Dániel Hegedűs, Vince Grolmusz: Robust Circuitry-Based Scores of Structural Importance of Human Brain Areas, PLOS One Vol. 19. No. 1 e0292613. https://doi.org/10.1371/journal.pone.0292613 (2024) [impact factor 3.752; Q1]
94, Vince Grolmusz: A Note on the LogRank Conjecture in Communication Complexity. Mathematics (2023), Vol. 11, 4651. https://doi.org/10.3390/math11224651 [impact factor 2.4; Q1].
93, Muntasir Kamal, Levon Tokmakjian, Jessica Knox, Peter Mastrangelo, Jingxiu Ji, Hao Cai, Jakub Wojciechowski, Micael P. Hughes, Kristof Takacs, Xiaoquan Chu, Jianfeng Pei, Vince Grolmusz, Malgorzata Kotulska, Julie Deborah Forman-Kay, Peter J. Roy: A Spatiotemporal Reconstruction of the C. elegans Pharyngeal Cuticle Reveals a Structure Rich in Phase-Separating Proteins, eLife, https://doi.org/10.7554/eLife.79396 (2022) [impact factor: 8.713; Q1, D1}
92, László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Discovering Sex and Age Implicator Edges in the Human Connectome, Neuroscience Letters Vol. 791, 136913 (2022) https://doi.org/10.1016/j.neulet.2022.136913 [impact factor 3.197];
91, László Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel, Vince Grolmusz: Succinct Amyloid and Non-Amyloid Patterns in Hexapeptides, ACS Omega Vol. 7, No. 40, 35532-35537 (2022), https://doi.org/10.1021/acsomega.2c02513 [impact factor: 4.132; Q1]
90, László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Introducing and Applying Newtonian Blurring: An Augmented Dataset of 126,000 Human Connectomes at braingraph.org, Scientific Reports, 12:3102 (2022), https://doi.org/10.1038/s41598-022-06697-4 [impact factor: 4.379; Q1, D1]
89, Balázs Szalkai, Vince Grolmusz: SCARF: A Biomedical Association Rule Finding Webserver, Journal of Integrative Bioinformatics, Vol. 19, No. 1. pp. 20210035, (2022) (an invited paper), https://doi.org/10.1515/jib-2021-0035 [SCOPUS D1]
88, Kristóf Takács, Vince Grolmusz: On the Border of the Amyloidogenic Sequences: Prefix Analysis of the Parallel Beta Sheets in the PDB_Amyloid Collection, Journal of Integrative Bioinformatics, Vol. 19, No. 1.[SCOPUS D1]
87, László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Identifying Super-Feminine, Super-Masculine and Sex-Defining Connections in the Human Braingraph, Cognitive Neurodynamics, Vol. 15. No. 6. pp. 949-959 (2021) https://doi.org/10.1007/s11571-021-09687-w [impact factor: 3.925],
86, Lászlo Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel and Vince Grolmusz: The Budapest Amyloid Predictor and its Applications, Biomolecules, 11(4) 500, (2021) https://doi.org/10.3390/biom11040500 [impact factor: 4.082]
85, Balázs Szalkai, Bálint Varga, Vince Grolmusz: The Graph of our Mind; Brain Sciences, Vol. 11, No. 3. 342 (2021) https://doi.org/10.3390/brainsci11030342 [impact factor 3.332]
84, Bálint Varga, Vince Grolmusz: The braingraph.org Database with more than 1000 Robust Human Structural Connectomes in Five Resolutions, Cognitive Neurodynamics Vol. 15 No. 5, pp. 915-919, (2021) https://doi.org/10.1007/s11571-021-09670-5 [impact factor: 3.925]
83, Kristóf Takács, Vince Grolmusz: The multiple alignments of very short sequences, FASEB BioAdvances, 2021;3:523-530, https://doi.org/10.1096/fba.2020-00118
82, Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Complete Subgraphs in the Human Connectome, PLOS ONE 15(8): e0236883 (2020) https://doi.org/10.1371/journal.pone.0236883 [impact factor 2.740; Q1]
81, Máté Fellner, Bálint Varga, Vince Grolmusz: Good Neighbors, Bad Neighbors: The Frequent Network Neighborhood Mapping of the Hippocampus Enlightens Structural Factors of the Human Intelligence; Scientific Reports Vol. 10. 11967 (2020) https://doi.org/10.1038/s41598-020-68914-2 [impact factor 4.011]
80, Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Network Neighborhood Mapping of the Human Hippocampus Shows Much More Frequent Neighbor Sets in Males Than in Females; PLOS ONE 15(1): e0227910 (2020). https://doi.org/10.1371/journal.pone.0227910 [impact factor 2.776]
79, Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Subgraphs of the Connectome of the Human Brain, Cognitive Neurodynamics Vol. 13, No. 5, pp. 453-460 (2019) https://doi.org/10.1007/s11571-019-09535-y https://rdcu.be/bAHoe [impact factor 3.021]
78, Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: High-Resolution Directed Human Connectomes and the Consensus Connectome Dynamics, PLOS ONE, Vol. 14 No. 4,: e0215473 (2019) https://doi.org/10.1371/journal.pone.0215473 [ impact factor 2.776]
77, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Comparing Advanced Graph-Theoretical Parameters of the Connectomes of the Lobes of the Human Brain, Cognitive Neurodynamics, Vol. 12, No. 6, pages 549-559 (2018), https://doi.org/10.1007/s11571-018-9508-y https://rdcu.be/8Gwh . [ impact factor 3.925]
76, Kristóf Takács, Bálint Varga, Vince Grolmusz: PDB_Amyloid: An Extended Live Amyloid Structure List from the PDB, FEBS Open Bio, Vol. 9, No. 1. pp. 185-190, 2019. https://doi.org/10.1002/2211-5463.12524 [impact factor 2.101]
75, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Mapping Correlations of Psychological and Connectomical Properties of the Dataset of the Human Connectome Project with the Maximum Spanning Tree Method, Brain Imaging and Behavior Vol. 13, No. 5, pp. 1185-1192 (2019), https://doi.org/10.1007/s11682-018-9937-6 , also available freely at this link. [impact factor 3.719]
74, Balázs Szalkai, Vince Grolmusz: MetaHMM: A Webserver for Identifying Novel Genes with Specified Functions in Metagenomic Samples; Genomics, Vol. 111, No. 4, pp. 883-885, (2019) https://doi.org/10.1016/j.ygeno.2018.05.016 [impact factor 3.16]
73, Balázs Szalkai, Vince Grolmusz: Human Sexual Dimorphism of the Relative Cerebral Area Volumes in the Data of the Human Connectome Project; European Journal of Anatomy, Vol. 22, No. 3. pp. 221-225 (2018)
72, Balázs Szalkai, Vince Grolmusz: SECLAF: A Webserver and Deep Neural Network Design Tool for Hierarchical Biological Sequence Classification, Bioinformatics, Vol 34, No. 14, pp. 2487-2489 2018 https://doi.org/10.1093/bioinformatics/bty116 [impact factor 7.30]
71, Csaba Kerepesi, Bálint Varga, Balázs Szalkai, Vince Grolmusz:The Dorsal Striatum and the Dynamics of the Consensus Connectomes in the Frontal Lobe of the Human Brain, Neuroscience Letters, Vol. 673, (2018), pp. 51-55. https://doi.org/10.1016/j.neulet.2018.02.052 [impact factor: 2.18]
70, Balázs Szalkai, Bálint Varga, Vince Grolmusz: The Robustness and the Doubly-Preferential Attachment Simulation of the Consensus Connectome Dynamics of the Human Brain, Scientific Reports, Vol. 7, 16118, https://doi.org/10.1038/s41598-017-16326-0 (2017) [impact factor: 4.25]
69, Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Comparative Connectomics: Mapping the Inter-Individual Variability of Connections within the Regions of the Human Brain, Neuroscience Letters Vol. 662, pp. 17-21, (2018) https://doi.org/10.1016/j.neulet.2017.10.003 [impact factor: 2.18].
68, Balázs Szalkai, Vince K. Grolmusz, Vince I. Grolmusz: Identifying Combinatorial Biomarkers by Association Rule Mining in the CAMD Alzheimer’s Database, Archives of Gerontology and Geriatrics Vol. 73, pp. 300-307 (2017), https://doi.org/10.1016/j.archger.2017.08.006 [impact factor: 2.08]
67, Balázs Szalkai, Vince Grolmusz: Near Perfect Protein Multi-Label Classification with Deep Neural Networks, Methods Vol. 132, pp. 50-56, (2018), https://doi.org/10.1016/j.ymeth.2017.06.034 [impact factor: 3.802]
66, Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz: The braingraph.org Database of High Resolution Structural Connectomes and the Brain Graph Tools, Cognitive Neurodynamics Vol. 11 No. 5, pp. 483-486 (2017) http://dx.doi.org/10.1007/s11571-017-9445-1 [impact factor: 2.159]
65, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Brain Size Bias Compensated Graph-Theoretical Parameters are Also Better in Women’s Structural Connectomes, Brain Imaging and Behavior Vol. 12, No. 3, pp. 663-673, (2018) http://dx.doi.org/10.1007/s11682-017-9720-0 [impact factor: 3.985]
64, Csaba Kerepesi, Vince Grolmusz: The “Giant Virus Finder” Discovers an Abundance of Giant Viruses in the Antarctic Dry Valleys, Archives of Virology (2017) Vol. 162, No. 6, pp. 1671-1676 http://dx.doi.org/10.1007/s00705-017-3286-4 [impact factor: 2.255]
63, Csaba Kerepesi, Judit E Szabó, Veronika Papp-Kádár, Orsolya Dobay, Dóra Szabó, Vince Grolmusz, Beata G Vertessy: Life without dUTPase, Frontiers in Microbiology, http://dx.doi.org/10.3389/fmicb.2016.01768 (2016) [impact factor: 4.165]
62, Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: Parameterizable Consensus Connectomes from the Human Connectome Project: The Budapest Reference Connectome Server v3.0, Cognitive Neurodynamics, 11(1), pp. 113-116, (2017) http://dx.doi.org/10.1007/s11571-016-9407-z [impact factor: 2.159]
61, Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz: How to Direct the Edges of the Connectomes: Dynamics of the Consensus Connectomes and the Development of the Connections in the Human Brain, PLoS One 11(6): e0158680. http://dx.doi.org/10.1371/journal.pone.0158680, June 30, 2016 [impact factor: 3.057]
60, Balázs Szalkai, Vince Grolmusz: Significant Differences Found in Short Nucleotide Sequences of Human Intestinal Metagenomes of Northern-European and Chinese Origin, Biochimica et Biophysica Acta (BBA) – General Subjects, Vol. 1861 (2017), Issue 1, Part B, https://doi.org/10.1016/j.bbagen.2016.06.019 January 2017, pp. 3627–3631. [impact factor: 5.083]
59, Balázs Szalkai, Vince Grolmusz: Nucleotide 9-mers Characterize the Type II Diabetic Gut Metagenome; Genomics, Vol. 107 (2016) pp. 120-123, http://dx.doi.org/10.1016/j.ygeno.2016.02.007 [impact factor: 2.284]
58, Gábor Iván, Dániel Bánky, Vince Grolmusz: Fast and Exact Sequence Alignment with the Smith-Waterman Algorithm: The SwissAlign Webserver; Gene Reports, Vol. 4, September 2016, pages 26-28. http://dx.doi.org/10.1016/j.genrep.2016.02.004
57, Csaba Kerepesi, Vince Grolmusz: Evaluating the Quantitative Capabilities of Metagenomic Analysis Software, Current Microbiology, Vol. 72. No. 5. pp. 612-616 (2016), http://dx.doi.org/10.1007/s00284-016-0991-2 [impact factor: 1.423]
56, Csaba Kerepesi, Vince Grolmusz: Giant Viruses of the Kutch Desert, Archives of Virology, Vol. 161 (2016), No.3 pp.721-724, http://dx.doi.org/10.1007/s00705-015-2720-8 [impact factor: 2.390].
55, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Graph Theoretical Analysis Reveals: Women’s Brains Are Better Connected than Men’s. PLoS ONE 10(7): e0130045 (2015) http://dx.doi.org/10.1371/journal.pone.0130045 [impact factor: 3.234]
54, Vince Grolmusz: Identifying Diabetes-Related Important Protein Targets with few Interacting Partners with the PageRank Algorithm, Royal Society Open Science, 2:140252, (2015) doi: http://dx.doi.org/10.1098/rsos.140252.
53, Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: The Budapest Reference Connectome Server v2.0, Neuroscience Letters, Vol. 595 (2015), Pages 60-62, http://dx.doi.org/10.1016/j.neulet.2015.03.071, [impact factor: 2.055]
52, Vince Grolmusz.: A Note on the PageRank of Undirected Graphs, Information Processing Letters 115 (2015), pp. 633-634. http://dx.doi.org/10.1016/j.ipl.2015.02.015, [impact factor: 0.479]
51, Kata Horváti, Bernadett Bacsa, Nóra Szabó, Kinga Fodor, Gyula Balka, Miklós Rusvai, Éva Kiss, Gábor Mező, Vince Grolmusz, Beáta Vértessy, Ferenc Hudecz, Szilvia Bősze: Antimycobacterial activity of peptide conjugate of pyridopyrimidine derivative against Mycobacterium tuberculosis in a series of in vitro and in vivo models, Tuberculosis, Vol. 95, Suppl. 1, June 2015, pp. S207-S211, http://dx.doi.org/10.1016/j.tube.2015.02.026 [impact factor: 3.5]
50, Csaba Kerepesi, Balázs Szalkai, Vince Grolmusz. Visual Analysis of the Quantitative Composition of Metagenomic Communities: the AmphoraVizu Webserver, Microbial Ecology Vol. 69 (2015) pp. 695-697, https://doi.org/10.1007/s00248-014-0502-6 [impact factor: 3.118].
49, Gábor Iván, Vince Grolmusz. On Dimension reduction of clustering results in structural bioinformatics, Biochimica et Biophysica Acta (BBA)- Proteins and Proteomics 1844 (2014), pp. 2277-2283, https://doi.org/10.1016/j.bbapap.2014.08.015 [impact factor: 3.733].
48, Balázs Szalkai, Ildikó Scheer, Kinga Nagy, Beáta G Vértessy, Vince Grolmusz, The Metagenomic Telescope, PLoS One, Vol. 9, No. 7, e101605 (2014). http://dx.doi.org/10.1371/journal.pone.0101605 [impact factor: 3.53]
47, Dániel Bánky, Balázs Szalkai, Vince Grolmusz: An Intuitive Graphical Webserver for Multiple-Choice Protein Sequence Search; Gene, 2014, Vol. 539 No. 1. pp. 152-3. http://dx.doi.org/10.1016/j.gene.2014.02.007 [impact factor: 2.19].
46, Rafael Ördög, Dániel Bánky, Balázs Szerencsi, Péter Juhász, Vince Grolmusz, The Erdős webgraph server, Discrete Applied Mathematics, Vol. 167 No. 20. April 2014, pp. 315-317, http://dx.doi.org/10.1016/j.dam.2013.10.032. (http://www.sciencedirect.com/science/article/pii/S0166218X13004757) [impact factor: 0.718]
45, Csaba Kerepesi, Dániel Bánky, Vince Grolmusz: AmphoraNet: The Webserver Implementation of the AMPHORA2 Metagenomic Workflow Suite, Gene, Vol. 539, No. 1, pp. 152-153, April 2014, http://dx.doi.org/10.1016/j.gene.2013.10.015 [impact factor: 2.19]
44, Orsolya Barabás, Veronika Németh, Andrea Bodor, András Perczel, Edina Rosta, Zoltán Kele, Imre Zagyva, Zoltán Szabadka, Vince I Grolmusz, Matthias Wilmanns, Beáta G Vértessy: Catalytic mechanism of α-phosphate attack in dUTPase is revealed by X-ray crystallographic snapshots of distinct intermediates, 31P-NMR spectroscopy and reaction path modelling, Nucleic Acids Research, Vol. 41, No. 22, pp. 10542–10555, December 2013, doi: https://doi.org/10.1093/nar/gkt756 [impact factor: 8.27]
43, Dániel Bánky, Gábor Iván, Vince Grolmusz: Equal Opportunity for Low-Degree Network Nodes: A PageRank-Based Method for Protein Target Identification in Metabolic Graphs, PLoS ONE 8(1): e54204. https://doi.org/10.1371/journal.pone.0054204, published 29 Jan 2013 [impact factor: 4.01]
42, Lilla Tóthmérész, Vince Grolmusz: Characterizing the Functional Similarity of Enzymes with high Co-Citation in Interaction Networks, Protein and Peptide Letters, Vol. 20, 2013, pp. 1181-1187 https://doi.org/10.2174/0929866511320100013 [impact factor:1.9]
41, Kata Horváti, Bernadett Bacsa, Nóra Szabó, Sándor Dávid, Gábor Mező, Vince Grolmusz, Beáta Vértessy, Ferenc Hudecz, and Szilvia Bősze: Enhanced Cellular Uptake of a New, in Silico Identified Antitubercular Candidate by Peptide Conjugation, Bioconjugate Chem.,2012, 23 (5), pp 900–907 https://doi.org/10.1021/bc200221t [impact factor: 5.002]
40, Christoph Scheich, Zoltán Szabadka, Beáta Vértessy, Vera Pütter, Vince Grolmusz, Markus Schade: Discovery of Novel MDR-Mycobacterium tuberculosis Inhibitor by New FRIGATE Computational Screen. PLoS ONE 6(12): e28428. https://doi.org/10.1371/journal.pone.0028428 (2011).
[impact factor: 4.3]
39, Árpád Tóth, Dániel Bánky, and Vince Grolmusz: Mathematical modeling and computer simulation of Brownian motion and hybridization of nanoparticle-bioprobe-polymer complexes in the low concentration limit, Molecular Simulation, Vol. 38, No. 1. pp. 66-71, https://doi.org/10.1080/08927022.2011.602217. [impact factor: 1.2]
38, Árpád Tóth, Dániel Bánky, and Vince Grolmusz: 3D Brownian Motion Simulator for High-Sensitivity Nano-Biotechnological Applications, IEEE Transactions on Nanobioscience, Vol. 10, No. 4. pp. 248-249, https://doi.org/10.1109/TNB.2011.2169331. p. 2 [impact factor 1.7]
37, Gábor Iván, Vince Grolmusz: When the Web Meets the Cell: Using Personalized PageRank for Analyzing Protein Interaction Networks, Bioinformatics, Vol. 27, No. 3. pp. 405-407 (2011) https://doi.org/10.1093/bioinformatics/btq680 [impact factor: 4.9]
36, Gábor Iván, Zoltán Szabadka, Vince Grolmusz: Cysteine and Tryptophan Anomalies Found when Scanning all the Binding Sites in the Protein Data Bank, International Journal of Bioinformatics Research and Applications, Vol. 6, No. 6, 2010, pp. 594-608, https://doi.org/10.1504/ijbra.2010.03874.
35, Gábor Iván, Zoltán Szabadka, Vince Grolmusz: A Hybrid Clustering of Protein Binding Sites FEBS Journal Vol. 277, No. 6. pp. 1494-1502 (2010). https://doi.org/10.1111/j.1742-4658.2010.07578.x [impact factor: 3.0]
34, Gábor Iván, Zoltán Szabadka, Vince Grolmusz: On the asymmetry of the residue compositions of the binding sites on protein surfaces; Journal of Bioinformatics and Computational Biology, Vol. 7. No. 6. (2009) pp. 931-938, https://doi.org/10.1142/S0219720009004394
33, Rafael Ördög, Zoltán Szabadka, Vince Grolmusz: DECOMP: A PDB decomposition tool on the web, Bioinformation Vol. 3 No. 10. pp. 413-414 (2009) https://doi.org/10.6026/97320630003413
32, Dániel Bánky, Rafael Ördög, Vince Grolmusz: NASCENT: An automatic protein interaction network generation tool for non-model organisms. Bioinformation Vol. 3 No. 8. pp. 361-363 (2009) https://doi.org/10.6026/97320630003361
31, Gábor Iván, Zoltán Szabadka, Rafael Ördög, Vince Grolmusz, Gábor Náray-Szabó: Four Spatial Points That Define Enzyme Families, Biochemical and Biophysical Research Communications, Vol. 383, No. 4, pp. 417-420, (2009) https://doi.org/10.1016/j.bbrc.2009.04.022 [impact factor: 2.5]
30, K. Hill, C.B. Pénzes, B.G. Vértessy, Z. Szabadka, V. Grolmusz, É. Kiss: Amphiphilic Nature of New Antitubercular Drug Candidates and Their Interaction with Lipid Monolayer, Progr Colloid Polym Sci (2008) 135: 87–92, https://doi.org/10.1007/2882_2008_117
29, Grolmusz, V.: Modular Representations of Polynomials: Hyperdense Coding and Fast Matrix Multiplication. IEEE Transactions on Information Theory, Volume 54, Issue 8, Aug. 2008 pp.:3687 – 3692; https://doi.org/10.1109/TIT.2008.926346 [impact factor: 2.4]
28, Szabadka, Z., Ördög, R., Grolmusz, V.: : The Ramachandran Map of More Than 6,500 Perfect Polypeptide Chains,
Biophysical Reviews and Letters, Vol 2, No. 3/4 (2007), pp. 267-271, https://doi.org/10.1142/S1793048007000519
27, Ordog, R., Szabadka, Z., Grolmusz, V.: Analyzing the Simplicial Decomposition of Spatial Protein Structures; BMC Bioinformatics, 2008, 9 (Suppl 1):S11 https://doi.org/10.1186/1471-2105-9-S1-S11, [impact factor: 3.4]
26, Szabadka, Z., Iván, G., Grolmusz, V.: Being a Binding-Site: Characterizing Residue-Composition of Binding Sites on Proteins, Bioinformation 2(5), 216-221 (2007), https://dx.doi.org/10.6026%2F97320630002216
25, Szabadka, Z., Grolmusz, V.: High Throughput Processing of the Structural Information of the Protein Data Bank, Journal of Molecular Graphics and Modeling 25 (2007) pp. 831-836. https://doi.org/10.1016/j.jmgm.2006.08.004 [impact factor:2.2]
24, Grolmusz, V.: Pairs of Codes with Prescribed Hamming Distances and Coincidences, Designs, Codes and Cryptography, Vol 41 (2006) , No. 1., pp. 87-99, https://doi.org/10.1007/s10623-006-0016-4
23, Grolmusz, V.: Co-Orthogonal Codes, Designs, Codes and Cryptography, Vol. 38, No. 3 (2006) pp. 363-372, https://doi.org/10.1007/s10623-005-1495-4
22, Grolmusz, V.: Computing Elementary Symmetric Polynomials with a Sub-Polynomial Number of Multiplications, SIAM Journal on Computing, Vol. 32, No. 6 (2003), pp 1475-1487, https://doi.org/10.1137/S009753970342465X
21, Grolmusz, V.: A Note on Set Systems with no Union of Cardinality 0 Modulo m, Discrete Mathematics and Theoretical Computer Science (DMTCS) Vol 6, No. 1 (2003), pp 41-44.
20, Grolmusz, V., Tardos, G.: A Note on Non-Deterministic Communication Complexity with Few Witnesses, Theory of Computing Systems, Vol 36, No. 4 (2003), pp 387-391, https://doi.org/10.1007/s00224-003-1158-7
19, Grolmusz, V.: A Note on Explicit Ramsey Graphs and Modular Sieves, Combinatorics, Probability and Computing Vol. 12, (2003) pp. 565-569 (an invited paper), https://doi.org/10.1017/S0963548303005698
18, Grolmusz, V.: Constructing Set-Systems with Prescribed Intersection Sizes, Journal of Algorithms, Vol. 44 (2002), pp. 321-337, https://doi.org/10.1016/S0196-6774(02)00204-3
17, Grolmusz, V., Sudakov, B.: On k-wise Set-Intersections and k-wise Hamming-Distances, J. Combin. Theory Ser. A 99 (2002), no. 1, 180–190, https://doi.org/10.1006/jcta.2002.3264
16, Grolmusz, V.: Set-Systems with Restricted Multiple Intersections, Electronic Journal of Combinatorics, Vol. 9, (2002), No. 1, R8, https://doi.org/10.37236/1625
15, Grolmusz, V.: A Degree-Decreasing Lemma for (MOD q-MOD p) Circuits, Discrete Mathematics and Theoretical Computer Science (DMTCS) Vol. 4. (2001) No. 2. pp. 247-254.
14, Grolmusz, V.: Low-Rank Co-Diagonal Matrices and Ramsey-Graphs, The Electronic Journal of Combinatorics, Vol. 7, (2000), No. 1, R15, https://doi.org/10.37236/1493
13, Grolmusz, V.: Superpolynomial Size Set-Systems with Restricted Intersections mod 6 and Explicit Ramsey Graphs, Combinatorica, Vol. 20, (2000), No. 1, pp. 73-88, https://doi.org/10.1007/s004930070032
12, Grolmusz, V., Tardos, G.: Lower Bounds for (MOD p, MOD m) Circuits, SIAM Journal on Computing, Vol. 29, (2000), No. 4, pp. 1209-1222, https://doi.org/10.1137/S0097539798340850
11, Grolmusz, V.: A lower bound for depth-3 circuits with mod m gates, Information Processing Letters Vol. 67, (1998), pp. 87-90, https://doi.org/10.1016/S0020-0190(98)00093-3
10, Grolmusz, V.: Harmonic Analysis, Real Approximation, and the Communication Complexity of Boolean Functions, Algorithmica, Vol. 23, (1999) No. 4, pp. 341-353 (an invited paper), https://doi.org/10.1007/PL00009265
9, Grolmusz, V.: Circuits and Multi-Party Protocols, Computational Complexity, Vol. 7, (1998), pp. 1-18, https://doi.org/10.1007/PL00001592
8, Grolmusz, V.: On the Power of Circuits with Gates of Low L_1 Norms, Theoretical Computer Science A, Vol. 188, (1997), pp. 117-127, https://doi.org/10.1016/S0304-3975(96)00290-3
7, Grolmusz, V.: Separating the Communication Complexities of MOD m and MOD p Circuits, Journal of Computer and Systems Sciences, Vol. 51, (1995), No. 2, https://doi.org/10.1006/jcss.1995.1069
6, Grolmusz, V.: On the Weak MOD-m Representation of Boolean Functions, Chicago Journal of Theoretical Computer Science, (CJTCS), Vol. 1, (1995), Article 2 http://dx.doi.org/10.4086/cjtcs.1995.002
5, Grolmusz, V.: The BNS Lower Bound for Multi–Party Protocols is Nearly Optimal, Information and Computation, Vol. 112, (1994) No. 1, pp. 51–54, https://doi.org/10.1006/inco.1994.1051
4, Grolmusz, V.: On a Ramsey-Theoretic Property of Orders, Journal of Combinatorial Theory, Ser. A, Vol. 61, (1992), No. 2, pp. 243–251, https://doi.org/10.1016/0097-3165(92)90021-L
3, Grolmusz, V.: On Mathematical Rigorousness, Magyar Filozófiai Szemle, (1992) No. 1-2, pp. 9-15 (in Hungarian) http://members.iif.hu/visontay/ponticulus/rovatok/limes/grolmusz.html
2, Grolmusz, V.: Large Parallel Machines Can be Extremely Slow for Small Problems; Algorithmica, Vol. 6, (1991), pp. 479-489, https://doi.org/10.1007/BF01759055
1, Grolmusz, V., Ragde P.: Incomparability in Parallel Computation; Discrete Applied Mathematics, Vol. 29 (1990), No. 1. pp. 63–78, https://doi.org/10.1016/0166-218X(90)90082-N
Conference Proceedings:
20, Máté Fellner, Bálint Varga, Vince Grolmusz, “The Frequent Complete Subgraphs in the Human Connectome”, In: Rojas I., Joya G., Catala A. (eds) Advances in Computational Intelligence. IWANN 2019. Lecture Notes in Computer Science, vol 11507. pp. 908-920, Springer
19, Takacs, K., B. Varga, and V. Grolmusz. “An automatically refreshed public list of amyloid and pre-amyloid structures from the PDB.” FEBS OPEN BIO. Vol. 8. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2018.
18, Grolmusz, Vince, Kristof Takacs, and Balint Varga. “Amyloids and pre-amyloids from the PDB.” FASEB JOURNAL. Vol. 32. No. 1. 9650 ROCKVILLE PIKE, BETHESDA, MD 20814-3998 USA: FEDERATION AMER SOC EXP BIOL, 2018.
17. Gábor Iván, Vince Grolmusz: Designing universal oligonucleotides for DNA/nanoparticle conjugates, Proc. Nanotech 2010 (Nanotechnology 2010: Electronics, Devices, Fabrication, MEMS, Fluidics and Computational), June 21-24, 2010, Anaheim, California; NSTI 2010, pages 573-576.
16. Rafael Ördög, Vince Grolmusz: On the bond graphs in the Delaunay-tetrahedra of the simplicial decomposition of spatial protein structures; Proceedings of the International Workshop on Practical Applications of Computational Biology & Bioinformatics (IWPACBB’09) LNCS 5518, pp. 1162-1169, University of Salamanca, June 10-12, 2009; DOI: 10.1007/978-3-642-02481-8_176
15. Rafael Ördög, Vince Grolmusz: Evaluating Genetic Algorithms in Protein-Ligand Docking, Proc. Bioinformatics Research and Applications, Atlanta, GA, 2008, LNCS Vol. 4983/2008, pp. 402-413, DOI: 10.1007/978-3-540-79450-9
14. Szabadka, Z., Grolmusz, V.: Building a Structured PDB: The RS-PDB Database. Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, Aug. 30-Sept 3, 2006., pp. 5755-5758.
13. Grolmusz, V.: On some applications of randomized memory. Proceedings of the GRACO2005, Angra dos Reis, Brazil, 27-29 April 2005. Electronic Notes in Discrete Mathematics, Vol. 19, 2005, pp. 203-209
12. Vince Grolmusz: Defying Dimensions Modulo 6 Proceedings of Computability in Europe (CiE) 2005 : “New Computational Paradigms” held in Amsterdam in June 2005, pages 78-81,
11. Grolmusz, V., Király, Z.: Generalized Secure Routerless Routing, Proceedings of the 4th International Conference on Networking, (ICN) Reunion Island, France, April 17-21, 2005, LNCS No. 3421, pp. 454-462;
10. Grolmusz, V., Király, Z.: Secure Routerless Routing, Proceedings of the Workshop “Future Directions in Network Architectures 2004” of the SIGCOMM’04 Conference, Portland, Oregon, August 30-September 3 2004, ACM Press
9, Grolmusz, V.: Co-Orthogonal Codes, Proceedings of the COCOON’2002, Singapore, August, 2002, LNCS 2387, pp. 144-152
8, Grolmusz, V.: Constructive Upper Bounds for Intersecting Set Systems. Proceedings of the Brazilian Symposium on Graphs, Algorithms and Combinatorics, Fortaleza, Ceará, Brazil, 2001. Electronic Notes in Discrete Mathematics Vol 7. http://www.elsevier.nl/gej-ng/31/29/24/39/23/show/Products/notes/index.htt#026
7, Grolmusz, V., Tardos, G.: Lower Bounds for (MOD p, MOD m) Circuits, Proceedings of FOCS’98, Palo Alto, California, November 1998, pp. 279-289.
6, Grolmusz, V.: A Degree-Decreasing Lemma for (MOD q, MOD p) Circuits, Proceedings of ICALP’98, Aalborg, Denmark, July 1998, LNCS 1443, pp. 215-222.
5, Grolmusz, V.: On Set Systems with Restricted Intersections Modulo a Composite Number, Proceedings of COCOON’97, Shanghai, August 20-22, 1997, LNCS 1276, pp. 82-90.
4, Grolmusz, V.: Harmonic Analysis, Real Approximation, and the Communication Complexity of Boolean Functions, Proceedings of the COCOON’96 Conference, Hong Kong, June 1996, LNCS 1090, pp. 142-151.
3, Grolmusz, V.: A Weight–Size Trade–Off for Circuits with MOD m Gates, Proceedings of the 26th ACM Symposium on Theory of Computing (STOC), Montreal, 1994, pp. 68-74
2, Grolmusz, V.: Separating the Communication Complexities of MOD m and MOD p Circuits, Proceedings of the 33rd Annual Symposium on Foundations of Computer Science (FOCS), Pittsburgh, 1992, pp. 278-287
1, Grolmusz V., Ragde P.: Incomparability in Parallel Computation; Proceedings of the 28th Annual Symposium on Foundations of Computer Science (FOCS), Los Angeles 1987, pp. 89-98,
Technical Reports:
50, László Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel, Vince Grolmusz: The Budapest Amyloid Predictor and its Applications, arXiv preprint arXiv 2011:03759 (2020)
49, László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Introducing and Applying Newtonian Blurring: An Augmented Dataset of 126,000 Human Connectomes at braingraph.org, arXiv preprint arXiv:2010.09568 (2020)
48, Bálint Varga, Vince Grolmusz: The braingraph.org Database with more than 1000 Robust Human Structural Connectomes in Five Resolutions, arXiv preprint arXiv:2008.13273 (2020)
47,Kristóf Takács, Vince Grolmusz: On the Border of the Amyloidogenic Sequences: Prefix Analysis of the Parallel Beta Sheets in the PDB_Amyloid Collection arXiv preprint arXiv:2003:02942 (2020)
46, László Keresztes, Evelin Szögi, Bálint Varga, Vince Grolmusz: Identifying Super-Feminine, Super-Masculine and Sex-Defining Connections in the Human Braingraph, arXiv preprint arXiv:1912:02291
45, Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Complete Subgraphs in the Human Connectome, arXiv preprint arXiv:1903.05979
44, Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Network Neighborhood Mapping of the Human Hippocampus Shows Much More Frequent Neighbor Sets in Males Than in Females, arXiv preprint arXiv:1811.07423 (2018)
43, Kristóf Takács, Bálint Varga, Vince Grolmusz: PDB_Amyloid: An Extended Live Amyloid Structure List from the PDB, arXiv preprint arXiv:1805.09758 (2018)
42, Máté Fellner, Bálint Varga, Vince Grolmusz: The Frequent Subgraphs of the Connectome of the Human Brain, arXiv preprint arXiv:1711.11314 (2017)
41, Balázs Szalkai, Vince Grolmusz: MetaHMM: A Webserver for Identifying Novel Genes with Specified Functions in Metagenomic Samples, arXiv preprint arXiv:1710.10995 (2017)
40, Balázs Szalkai, Vince Grolmusz: SCARF: A Biomedical Association Rule Finding Webserver, arXiv preprint arXiv:1709.09850 (2017)
39, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Comparing Advanced Graph-Theoretical Parameters of the Connectomes of the Lobes of the Human Brain, arXiv preprint arXiv:1709.04974 (2017)
38, Balázs Szalkai, Vince Grolmusz: SECLAF: A Webserver and Deep Neural Network Design Tool for Biological Sequence Classification, arXiv preprint arXiv:1708.04103 (2017)
37, Balázs Szalkai, Vince Grolmusz: Near Perfect Protein Multi-Label Classification with Deep Neural Networks, arXiv preprint arXiv:1703.10663
36, Balázs Szalkai, Vince Grolmusz: The Robustness and the Doubly-Preferential Attachment Simulation of the Consensus Connectome Dynamics of the Human Brain, arXiv preprint arXiv:1610:04568
35, Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz: The braingraph.org Database of High Resolution Structural Connectomes and the Brain Graph Tools, arXiv preprint arXiv:1610:02016
34, Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: High-Resolution Directed Human Connectomes and the Consensus Connectome Dynamics, arXiv preprint arXiv:1609.09036 (2016)
33, Csaba Kerepesi, Bálint Varga, Balázs Szalkai, Vince Grolmusz:The Dorsal Striatum and the Dynamics of the Consensus Connectomes in the Frontal Lobe of the Human Brain arXiv preprint arXiv:1605.01441 (2016)
32, Balázs Szalkai, Vince Grolmusz: Human Sexual Dimorphism of the Relative Cerebral Area Volumes in the Data of the Human Connectome Project, arXiv preprint arXiv:1604.05992 (2016)
31, Balázs Szalkai, Bálint Varga, Vince Grolmusz: The Graph of Our Mind, arXiv preprint arXiv:1603.00904 (2016)
30, Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: Parameterizable Consensus Connectomes from the Human Connectome Project: The Budapest Reference Connectome Server v3.0, arXiv preprint arXiv:1602.04776 (2016);
29, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Mapping Correlations of Psychological and Connectomical Properties of the Dataset of the Human Connectome Project with the Maximum Spanning Tree Method arXiv preprint arXiv:1602.03008 (2016)
28, Balázs Szalkai, Bálint Varga, Vince Grolmusz: The Advantage is at the Ladies: Brain Size Bias-Compensated Graph-Theoretical Parameters are Also Better in Women’s Connectomes arXiv preprint arXiv:1512.01156 (2015)
27, Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz: How to Direct the Edges of the Connectomes: Dynamics of the Consensus Connectomes and the Development of the Connections in the Human Brain , arXiv:1509.05703 (2015)
26, Csaba Kerepesi, Judit E. Szabó, Vince Grolmusz, Beáta G. Vértessy: Life without dUTPase. arXiv preprint arXiv:1509.04850 (2015)
25, Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Comparative Connectomics: Mapping the Inter-Individual Variability of Connections within the Regions of the Human Brain, arXiv preprint 1507.00327 (2015)
24, Csaba Kerepesi, Vince Grolmusz: The “Giant Virus Finder” Discovers an Abundance of Giant Viruses in the Antarctic Dry Valleys, arXiv preprint arXiv:1503.05575 (2015)
23, Balázs Szalkai, Bálint Varga, Vince Grolmusz: Graph Theoretical Analysis Reveals: Women’s Brains are Better Connected than Men’s; arXiv preprint arXiv:1501.00727 (2015)
22, Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz: The Budapest Reference Connectome Server Ver. 2.0, arXiv preprint arXiv:1412.3151 (2014)
21, Csaba Kerepesi, Vince Grolmusz: Giant viruses of the Kutch desert; arXiv preprint, arXiv 1410:1278, October 7, 2014.
20, Ivan, G., Bánky, D., Grolmusz, V.:Fast and Exact Sequence Alignment with the Smith-Waterman Algorithm: The SwissAlign Webserver, arXiv:1309.1895 September 7, 2013
19, Ivan, G., Grolmusz, V.: Dimension reduction of clustering results in bioinformatics, arXiv:1309.1892, September 7, 2013
18, Grolmusz, V.: A Note on the PageRank of Undirected Graphs, arXiv 1205.1960, May 10, 2012
17, Grolmusz, V.: Defying Dimensions Modulo 6, ECCC Report TR03-058
16, Grolmusz, V.: Near Quadratic Matrix Multiplication Modulo Composites , ECCC Report TR03-001,
15, Grolmusz, V.: Computing Elementary Symmetric Polynomials with a Sub-Polynomial Number of Multiplications, ECCC Report TR02-052,
14, Grolmusz, V.: Pairs of Codes with Prescribed Hamming Distances and Coincidences, DIMACS Technical Report No. 2002-09
13, Grolmusz, V.: A Trade-Off for Covering the Off-Diagonal Elements of Matrices, DIMACS Technical Report No. 2002-01
12, Grolmusz, V., Sudakov, B.: k-wise Set-Intersections and k-wise Hamming-Distances, DIMACS Technical Report No. 2001-11. (ftp://dimacs.rutgers.edu/pub/dimacs/TechnicalReports/ TechReports/2001/2001-11.ps.gz)
11, Grolmusz, V.: Set-Systems with Restricted Multiple Intersections and Explicit Ramsey Hypergraphs, DIMACS Technical Report No. 2001-04 (ftp://dimacs.rutgers.edu/pub/dimacs/TechnicalReports/ TechReports/2001/2001-04.ps.gz)
10, Grolmusz, V.: Constructing Set-Systems with Prescribed Intersection Sizes, DIMACS Technical Report No. 2001-03 (ftp://dimacs.rutgers.edu/pub/~dimacs/TechnicalReports/TechReports/2001/2001-03.ps.gz)
9, Grolmusz, V.: A Note on Set Systems with no Union of Cardinality 0 Modulo m, DIMACS Technical Report No. 2000-11
(WWW: ftp://dimacs.rutgers.edu/pub/dimacs/TechnicalReports/TechReports/2000/2000-11.ps.gz )
8, Grolmusz, V., Tardos, G.: Lower Bounds for (MOD p, MOD m) Circuits, ECCC Report TR98-036, (WWW: ftp://ftp.eccc.uni-trier.de/pub/eccc/reports/1998/TR98-036/index.html)
7, Grolmusz, V.: On the Power of Circuits with Gates of Low L_1 Norms, ECCC Report TR95-046, (WWW: ftp://ftp.eccc.uni-trier.de/pub/eccc/reports/1995/TR95-046/index.html)
6, Grolmusz, V.: On Multi–Party Communication Complexity of Random Functions, Technical Report No. MPII-1993-162, December 1, 1993, Max Planck Institut fuer Informatik, 66123 Saarbruecken, Germany
5, Grolmusz, V.: Harmonic Analysis, Real Approximation, and the Communication Complexity of Boolean Functions, Technical Report No. MPII-1993-161, November 22, 1993, Max Planck Institut fuer Informatik, 66123 Saarbruecken, Germany
4, Grolmusz, V.: Mod m Gates do not Help on the Ground Floor, Technical Report No. MPII-1993-142, October 11, 1993, Max Planck Institut fuer Informatik, 66123 Saarbruecken, Germany
3, Grolmusz, V.: Multi-Party Protocols and Spectral Norms, Technical Report No. MPII-1993-132, August 13, 1993, Max Planck Institut fuer Informatik, 66123 Saarbruecken, Germany
2, Grolmusz, V.: Separating the Communication Complexities of MOD m and MOD p Circuits, Technical Report No. MPII-1992-120, May 26, 1992, Max Planck Institut fuer Informatik, 66123 Saarbruecken, Germany
1, Grolmusz, V.: Circuits and Multi-Party Protocols, Technical Report No. MPII-1992-104, January 30, 1992, Max Planck Institut fuer Informatik, 66123 Saarbruecken, Germany
Published Patents:
| WO2011089456 | NOVEL MEDICINAL COMPOUNDS | |
| WO2011089457 | NOVEL MEDICINAL COMPOUNDS | |
| 20080194415 | Method for structuring and cleaning steric macromolecular data |
| US Patent 7,606,847 |
Dense and randomized storage and coding of information | |
| 20050047516 | A method for dense and secure transmission of signals and information using a small number of channels |
Book Chapter:
Protein-Protein Interactions, 2011 Nova Publishers, Edited by P. Kangueane, ISBN: 978-1-61761-548-1, Chapter 7. NASCENT: An automatic protein interaction network generation tool for non-model organisms (Dániel Bánky, Rafael Ördög, Vince Grolmusz)