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D-Index & Metrics

Computer Science

D-Index
31
Citations
4857
World Ranking
13547
National Ranking
654

Ina Koch 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 Ina Koch sits on this spectrum.

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 publications 991+

This scientist: 112 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Ina Koch 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 Ina Koch sits on this spectrum.

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 D-Index 131+

This scientist: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Overview

Ina Koch is a researcher affiliated with Goethe University Frankfurt in Germany. Their academic work primarily focuses on Medicine and Biochemistry, Genetics and Molecular Biology, with significant contributions spanning 68 and 48 publications respectively.

Their subfields of study include Molecular Biology, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Oncology, and Pulmonary and Respiratory Medicine. This interdisciplinary approach is reflected in their research topics, which cover:

  • Radiomics and Machine Learning in Medical Imaging
  • Advanced X-ray and CT Imaging
  • Bioinformatics and Genomic Networks
  • AI in cancer detection
  • Gene Regulatory Network Analysis
  • Cell Image Analysis Techniques
  • Medical Imaging Techniques and Applications

Ina Koch has published multiple papers in well-recognized scientific venues. Frequent publication venues include Biological Chemistry, bioRxiv (Cold Spring Harbor Laboratory), Scientific Reports, Journal of Thoracic Oncology, and Biosystems. The number of publications in these venues ranges from two to four, indicating an active engagement with these journals.

Some of the recent publications authored or coauthored by Ina Koch are:

  • Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features, 2020, European Radiology
  • Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging, 2021, Scientific Reports
  • Variation of butyrate production in the gut microbiome in type 2 diabetes patients, 2023, International Microbiology
  • Evaluation of automatic discrimination between benign and malignant prostate tissue in the era of high precision digital pathology, 2023, BMC Bioinformatics
  • CT-radiomics and clinical risk scores for response and overall survival prognostication in TACE HCC patients, 2023, Scientific Reports

Their collaborations include frequent coauthors such as Jörg Ackermann, Thomas J. Vogl, Simon S. Martin, Simon Bernatz, and İbrahim Yel. These partnerships indicate a strong collaborative network across multiple areas of biomedical research.

Best Publications

  • Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

    Daniel J. Klionsky;Amal Kamal Abdel-Aziz;Sara Abdelfatah;Mahmoud Abdellatif

  • Complexome Profiling Identifies TMEM126B as a Component of the Mitochondrial Complex I Assembly Complex

    Heinrich Heide;Lea Bleier;Mirco Steger;Jörg Ackermann

  • Enumerating all connected maximal common subgraphs in two graphs

    Ina Koch

  • Increase of functional diversity by alternative splicing.

    Evgenia V. Kriventseva;Ina Koch;Rolf Apweiler;Martin Vingron

  • Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae

    Stefan Schuster;Thomas Pfeiffer;Ferdinand Moldenhauer;Ina Koch

  • Application of Petri net based analysis techniques to signal transduction pathways

    Andrea Sackmann;Monika Heiner;Ina Koch

  • Erratum to: Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer.

    Sören Müller;Susanne Raulefs;Philipp Bruns;Fabian Afonso-Grunz

  • Model validation of biological pathways using Petri nets--demonstrated for apoptosis.

    Monika Heiner;Ina Koch;Jürgen Will

  • Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber

    Ina Koch;Björn H. Junker;Monika Heiner

  • An Algorithm for Finding Maximal Common Subtopologies in a Set of Protein Structures

    Ina Koch;Thomas Lengauer;Egon Wanke

  • Steady State Analysis of Metabolic Pathways Using Petri Nets

    Klaus Voss;Monika Heiner;Ina Koch

  • Petri net based model validation in systems biology

    Monika Heiner;Ina Koch

  • Modeling in Systems Biology: The Petri Net Approach

    Ina Koch;Wolfgang Reisig;Falk Schreiber

  • Modularization of biochemical networks based on classification of Petri net t-invariants

    Eva Grafahrend-Belau;Falk Schreiber;Monika Heiner;Andrea Sackmann

  • Petri net modelling of gene regulation of the Duchenne muscular dystrophy.

    Stefanie Grunwald;Astrid Speer;Jörg Ackermann;Ina Koch

  • APADB: a database for alternative polyadenylation and microRNA regulation events

    Sören Müller;Lukas Rycak;Fabian Afonso-Grunz;Peter Winter

  • NOVA: a software to analyze complexome profiling data.

    Heiko Giese;Jörg Ackermann;Heinrich Heide;Lea Bleier

  • Analysis of protein sheet topologies by graph theoretical methods

    Ina Koch;Frieder Kaden;Joachim Selbig

  • An analysis of the Petri net based model of the human body iron homeostasis process

    Andrea Sackmann;Dorota Formanowicz;Piotr Formanowicz;Ina Koch

  • omiRas: a Web server for differential expression analysis of miRNAs derived from small RNA-Seq data

    Sören Müller;Lukas Rycak;Peter Winter;Günter Kahl

  • Whither Systems Medicine

    Rolf Apweiler;Tim Beissbarth;Michael R. Berthold;Nils Blüthgen

  • Model Validation of Biological Pathways Using Petri Nets - Demonstrated for Apoptosis

    Monika Heiner;Ina Koch;Jürgen Will

Frequent Co-Authors

Monika Heiner
Monika Heiner Brandenburg University of Technology
Heinz D. Osiewacz
Heinz D. Osiewacz Goethe University Frankfurt
Stefan Schuster
Stefan Schuster Friedrich Schiller University Jena
Sven Cichon
Sven Cichon University of Basel
Ilka Wittig
Ilka Wittig Goethe University Frankfurt
Ulrich Brandt
Ulrich Brandt Radboud University
Christine M. Freitag
Christine M. Freitag Goethe University Frankfurt
Stefan Herms
Stefan Herms University of Basel
Oliver Eickelberg
Oliver Eickelberg University of Pittsburgh
Jan O. Korbel
Jan O. Korbel European Molecular Biology Laboratory

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