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Natasa Przulj
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Computer Science
Spain
2025

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 44 7470 7251 97 95 89 10112

Natasa Przulj publications per year

The chart shows the history of publications by Natasa Przulj between 1998 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Natasa Przulj published across 28 years, from 1998 to 2025, averaging 4.5 papers a year. Output peaked at 12 publications in 2010. 16 of the 126 publications appeared in the last two years.

No. of publications
5 10
Bar chart. Horizontal axis: year, 1998 to 2025. Vertical axis: number of publications, 0 to 12. Peak 12 publications in 2010. 1998: 1 publication 1999: 0 publications 2000: 1 publication 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 4 publications 2005: 3 publications 2006: 3 publications 2007: 1 publication 2008: 5 publications 2009: 5 publications 2010: 12 publications 2011: 9 publications 2012: 4 publications 2013: 3 publications 2014: 12 publications 2015: 8 publications 2016: 8 publications 2017: 4 publications 2018: 4 publications 2019: 3 publications 2020: 3 publications 2021: 4 publications 2022: 3 publications 2023: 10 publications 2024: 12 publications 2025: 4 publications
1998 2025

126 publications in total across all disciplines

View publications per year as a table
Natasa Przulj: publications per year, 1998 to 2025
Year Publications
1998 1
1999 0
2000 1
2001 0
2002 0
2003 0
2004 4
2005 3
2006 3
2007 1
2008 5
2009 5
2010 12
2011 9
2012 4
2013 3
2014 12
2015 8
2016 8
2017 4
2018 4
2019 3
2020 3
2021 4
2022 3
2023 10
2024 12
2025 4
Total 126
Download as CSV

Natasa Przulj publications per year - data summary

  • Natasa Przulj, a Computer Science scholar from Institució Catalana de Recerca i Estudis Avançats, has 126 publications recorded across 28 years, from 1998 to 2025.
  • The oldest publication on record dates to 1998 and the most recent to 2025.
  • The most productive years are 2010, 2014 and 2024, with 12 publications each.
  • The least productive years with any output are 1998, 2000 and 2007, with 1 publication each.
  • 4 of the 28 years in the span carry no publications at all (1999, 2001, 2002 and 2003).
  • The rate of publication averages 4.5 papers per year over the whole span, or 5.3 per year counting only the 24 years with at least one publication.
  • The last 5 years on the chart (2021-2025) hold 33 publications, 26% of the career total.
  • Split into equal eras - 1998-2007: 13 publications (1.3 per year); 2008-2017: 70 publications (7.0 per year); 2018-2025: 43 publications (5.4 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

Natasa Przulj publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Natasa Przulj sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 82–91 publications, is where this scientist sits. 32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32–41 publications 991+

This scientist: 89 publications — 5th percentile

5% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324 89
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Natasa Przulj publication distribution in Computer Science in 2026 - data summary

  • The chart plots the publication count of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 97 ranges running from 32–41 to 991+ publications.
  • Natasa Przulj, a Computer Science scholar from Institució Catalana de Recerca i Estudis Avançats, records 89 publications - the 5th percentile of the discipline.
  • 5% of ranked Computer Science scientists score the same or lower than Natasa Przulj, and about 95% score higher.
  • The median of the discipline falls in the 202–211 publications range, and Natasa Przulj ranks below the median.
  • The most crowded range is 142–151 publications, holding 609 scientists (4% of the field).
  • 70% of the field sits in the lowest quarter of the value range (up to 272–281 publications), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 991 publications or more, 100 scientists in all (<1% of the field).

Natasa Przulj D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Natasa Przulj sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 44–45 D-Index, is where this scientist sits. 30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30–31 D-Index 131+

This scientist: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763 44
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Natasa Przulj D-index placement in Computer Science in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 52 ranges running from 30–31 to 131+ D-Index.
  • Natasa Przulj, a Computer Science scholar from Institució Catalana de Recerca i Estudis Avançats, records 44 D-Index - the 48th percentile of the discipline.
  • 48% of ranked Computer Science scientists score the same or lower than Natasa Przulj, and about 52% score higher.
  • The median of the discipline falls in the 44–45 D-Index range, and Natasa Przulj falls inside that same range.
  • The most crowded range is 36–37 D-Index, holding 990 scientists (7% of the field).
  • 71% of the field sits in the lowest quarter of the value range (up to 54–55 D-Index), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 131 D-Index or more, 98 scientists in all (<1% of the field).

Research.com Recognitions

  • 2025 - Research.com Computer Science in Spain Leader Award
  • 2022 - Research.com Computer Science in Spain Leader Award
  • 2017 - Member of Academia Europaea

Overview

Natasa Przulj is affiliated with the Institució Catalana de Recerca i Estudis Avançats in Spain. Their research primarily contributes to the field of Biochemistry, Genetics and Molecular Biology, with a focus on Molecular Biology, Computational Theory and Mathematics, Neurology, Infectious Diseases, and Genetics.

The scientist's work encompasses a range of topics including Bioinformatics and Genomic Networks, Gene expression and cancer classification, Computational Drug Discovery Methods, Gene Regulatory Network Analysis, Genetics, Bioinformatics, and Biomedical Research, Parkinson's Disease Mechanisms and Treatments, and Biomedical Text Mining and Ontologies.

Recent publications by Natasa Przulj include:

  • Current and future directions in network biology, 2024, Bioinformatics Advances
  • Unveiling new disease, pathway, and gene associations via multi-scale neural network, 2020, PLoS ONE
  • Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing, 2024, Nucleic Acids Research
  • Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease, 2024, Scientific Reports
  • Chromatin network markers of leukemia, 2020, Bioinformatics

Frequent co-authors with whom Natasa Przulj has collaborated include Noël Malod-Dognin, Alexandros Xenos, Gaia Ceddia, Sam F. L. Windels, and Katarina Mihajlović.

The scientist has published extensively in several venues, with a notable presence in:

  • Bioinformatics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Bioinformatics Advances
  • PLoS ONE

Natasa Przulj's research covers areas related to the analysis and modeling of genomic networks, computational methods for drug discovery, and the application of multi-omics data integration to understand complex diseases like Parkinson's disease.

Among the recognitions received, Natasa Przulj became a Member of Academia Europaea in 2017.

Best Publications

  • A global genetic interaction network maps a wiring diagram of cellular function

    Michael Costanzo;Benjamin VanderSluis;Elizabeth N. Koch;Anastasia Baryshnikova

  • Evidence for Network Evolution in an Arabidopsis Interactome Map

    Matija Dreze;Anne-Ruxandra Carvunis;Benoit Charloteaux

  • High-throughput mapping of a dynamic signaling network in mammalian cells.

    Miriam Barrios-Rodiles;Kevin R. Brown;Barish Ozdamar;Barish Ozdamar;Rohit Bose;Rohit Bose

  • Protein complex prediction via cost-based clustering

    A. D. King;N. Pržulj;I. Jurisica

  • Functional topology in a network of protein interactions

    N. Pržulj;D.A. Wigle;I. Jurisica

  • Integrative network alignment reveals large regions of global network similarity in yeast and human

    Oleksii Kuchaiev;Nataša Pržulj

  • Methods for biological data integration: perspectives and challenges

    Vladimir Gligorijević;Nataša Pržulj

  • Optimal network alignment with graphlet degree vectors.

    Tijana Milenković;Tijana Milenković;Weng Leong Ng;Wayne Hayes;Wayne Hayes;Nataša Pržulj

  • Revealing the Hidden Language of Complex Networks

    Ömer Nebil Yaveroğlu;Noël Malod-Dognin;Darren Davis;Zoran Levnajic

  • Integrative methods for analyzing big data in precision medicine

    Vladimir Gligorijević;Noël Malod-Dognin;Nataša Pržulj

  • Geometric De-noising of Protein-Protein Interaction Networks

    Oleksii Kuchaiev;Marija Rasajski;Marija Rasajski;Desmond J. Higham;Natasa Przulj

  • Efficient estimation of graphlet frequency distributions in protein--protein interaction networks

    N. Pržulj;D. G. Corneil;I. Jurisica

  • Characterization of the proteasome interaction network using a QTAX-based tag-team strategy and protein interaction network analysis

    Cortnie Guerrero;Tijana Milenkovic;Natasa Przulj;Peter Kaiser

  • GraphCrunch: A tool for large network analyses

    Tijana Milenković;Jason Lai;Nataša Pržulj

  • L-GRAAL: Lagrangian graphlet-based network aligner.

    Noël Malod-Dognin;Nataša Pržulj

  • Network analytics in the age of big data

    Nataša Pržulj;Noël Malod-Dognin

  • Fitting a geometric graph to a protein–protein interaction network

    Desmond J. Higham;Marija Rašajski;Nataša Pržulj

  • Not all scale free networks are Born equal: the role of the seed graph in PPI network emulation

    Fereydoun Hormozdiari;Petra Berenbrink;Nataša Pržulj;Cenk Sahinalp

  • Dominating biological networks.

    Tijana Milenković;Vesna Memišević;Anthony Bonato;Nataša Pržulj

  • Modeling Interactome: Scale-Free or Geometric?

    Natasa Przulj;Derek G. Corneil;Igor Jurisica

  • Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data

    Tijana Milenković;Vesna Memišević;Anand K. Ganesan;Nataša Pržulj

  • Uncovering Biological Network Function via Graphlet Degree Signatures

    Tijana Milenkovic;Natasa Przulj

  • Proper evaluation of alignment-free network comparison methods

    Ömer Nebil Yaveroğlu;Tijana Milenković;Nataša Pržulj

  • Geometric evolutionary dynamics of protein interaction networks.

    Natasa Przulj;Oleksii Kuchaiev;Aleksandar Stevanovic;Wayne B. Hayes

  • A framework for FPGA acceleration of large graph problems: Graphlet counting case study

    Brahim Betkaoui;David B. Thomas;Wayne Luk;Natasa Przulj

  • Optimized null model for protein structure networks.

    Tijana Milenković;Ioannis Filippis;Michael Lappe;Nataša Pržulj

  • Bridging the gaps in systems biology.

    Marija Cvijovic;Joachim Almquist;Jonas Hagmar;Stefan Hohmann

  • Complementarity of network and sequence information in homologous proteins.

    Vesna Memisevic;Tijana Milenkovic;Natasa Przulj

  • An integrative approach to modeling biological networks.

    Vesna Memisevic;Tijana Milenkovic;Natasa Przulj

  • Anti-nicastrin monoclonal antibodies elicit pleiotropic anti-tumour pharmacological effects in invasive breast cancer cells

    Aleksandra Filipović;Ylenia Lombardo;Monica Fronato;Joel Abrahams

  • ergm.graphlets: A Package for ERG Modeling Based on Graphlet Statistics

    Ömer Nebil Yaveroğlu;Sean M. Fitzhugh;Maciej Kurant;Athina Markopoulou

  • Learning the structure of protein-protein interaction networks.

    Oleksii Kuchaiev;Natasa Przulj

Frequent Co-Authors

Desmond J. Higham
Desmond J. Higham University of Edinburgh
Andrew R. Green
Andrew R. Green University of Nottingham
R. Charles Coombes
R. Charles Coombes Imperial College London
Ian O. Ellis
Ian O. Ellis University of Nottingham
Anne J. Ridley
Anne J. Ridley University of Bristol
David E. Hill
David E. Hill Harvard University
Robert J. Schmitz
Robert J. Schmitz University of Georgia
Frederick P. Roth
Frederick P. Roth Lunenfeld-Tanenbaum Research Institute
Marc Vidal
Marc Vidal Harvard University
Jeffery L. Dangl
Jeffery L. Dangl University of North Carolina at Chapel Hill

External Links

Personal website of Natasa Przulj

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2027 Online Addiction Counseling Degree Programs Costs: Tuition & Fees
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2027 Best Online Master’s in Educational Administration Degree Programs
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2027 Most Affordable Online Artificial Intelligence Degree Programs
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2027 Online Speech Pathology Master's Degree Program Costs: Tuition & Fees
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2027 Online Adult Gerontology Acute Care Nurse Practitioner Doctorate Programs That Give Credit for Prior Graduate Work
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2027 Online Science Degree Master's Programs That Accept FAFSA
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2027 Most Affordable Online MBA in Finance Degree Programs
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2027 Best Value Online Fashion Design Degree Programs: Affordable Accredited Options with the Strongest ROI
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