World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
73
Citations
25953
World Ranking
5826
National Ranking
131

Engineering and Technology

D-Index
66
Citations
21699
World Ranking
1381
National Ranking
34

Rita Casadio publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Rita Casadio sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 349 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Rita Casadio D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Rita Casadio sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 66 D-Index — 86th percentile

86% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Rita Casadio is affiliated with the University of Bologna in Italy and has a research focus primarily within the fields of Biochemistry, Genetics, and Molecular Biology. The subfields of study associated with their work include Molecular Biology, Genetics, Cancer Research, Materials Chemistry, and Clinical Biochemistry.

The main topics of Casadio's research encompass Machine Learning in Bioinformatics, Genomics and Phylogenetic Studies, Protein Structure and Dynamics, RNA and Protein Synthesis Mechanisms, Genomics and Rare Diseases, Bioinformatics and Genomic Networks, and Genetics, Bioinformatics, and Biomedical Research.

Frequent coauthors collaborating with Casadio include Pier Luigi Martelli, Castrense Savojardo, Giulia Babbi, Matteo Manfredi, and Steven E. Brenner.

Casadio has published research in several prominent venues over their career, including Journal of Molecular Biology, Faculty Opinions - Post-Publication Peer Review of the Biomedical Literature, Human Genetics, bioRxiv (Cold Spring Harbor Laboratory), and Faculty of 1000 Research Ltd.

Some of Casadio's recent papers are:

  • "DOME: recommendations for supervised machine learning validation in biology," 2021, Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)
  • "Solvent Accessibility of Residues Undergoing Pathogenic Variations in Humans: From Protein Structures to Protein Sequences," 2021, Frontiers in Molecular Biosciences
  • "Machine learning solutions for predicting protein-protein interactions," 2022, Wiley Interdisciplinary Reviews Computational Molecular Science
  • "CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods," 2024, Genome Biology
  • "Biallelic variants in LIG3 cause a novel mitochondrial neurogastrointestinal encephalomyopathy," 2021, Brain

Best Publications

  • I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.

    Emidio Capriotti;Piero Fariselli;Rita Casadio

  • Transglutaminases: Nature’s biological glues

    Martin Griffin;Rita Casadio;Carlo M Bergamini

  • A large-scale evaluation of computational protein function prediction

    Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes

  • Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information

    E. Capriotti;R. Calabrese;R. Casadio

  • Topology prediction for helical transmembrane proteins at 86% accuracy.

    Burkhard Rost;Piero Fariselli;Rita Casadio

  • Functional annotations improve the predictive score of human disease-related mutations in proteins

    Remo Calabrese;Emidio Capriotti;Piero Fariselli;Pier Luigi Martelli

  • PredGPI: a GPI-anchor predictor

    Andrea Pierleoni;Pier Luigi Martelli;Rita Casadio

  • Transmembrane helices predicted at 95% accuracy

    Burkhard Rost;Rita Casadio;Piero Fariselli;Chris Sander

  • ConSeq: the identification of functionally and structurally important residues in protein sequences

    Carine Berezin;Fabian Glaser;Josef Rosenberg;Inbal Paz

  • Algorithms in Bioinformatics

    Rita Casadio;Gene Myers

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • BUSCA: an integrative web server to predict subcellular localization of proteins.

    Castrense Savojardo;Pier Luigi Martelli;Piero Fariselli;Giuseppe Profiti;Giuseppe Profiti

  • BaCelLo: a Balanced subCellular Localization predictor.

    Andrea Pierleoni;Pier Luigi Martelli;Piero Fariselli;Rita Casadio

  • WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation

    Emidio Capriotti;Remo Calabrese;Piero Fariselli;Pier Luigi Martelli

  • Prediction of protein--protein interaction sites in heterocomplexes with neural networks.

    Piero Fariselli;Florencio Pazos;Alfonso Valencia;Rita Casadio

  • A three-state prediction of single point mutations on protein stability changes

    Emidio Capriotti;Piero Fariselli;Ivan Rossi;Rita Casadio

  • Prediction of coordination number and relative solvent accessibility in proteins.

    Gianluca Pollastri;Pierre Baldi;Pietro Fariselli;Rita Casadio

  • A high‐density, SNP‐based consensus map of tetraploid wheat as a bridge to integrate durum and bread wheat genomics and breeding

    Marco Maccaferri;Andrea Ricci;Silvio Salvi;Sara Giulia Milner

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Piero Fariselli
Piero Fariselli University of Turin
Luca Fontanesi
Luca Fontanesi University of Bologna
David T. Jones
David T. Jones University College London
Olivier Lichtarge
Olivier Lichtarge Baylor College of Medicine
Predrag Radivojac
Predrag Radivojac Northeastern University
Steven E. Brenner
Steven E. Brenner University of California, Berkeley
Vincenzo Russo
Vincenzo Russo University of Bologna
Sean D. Mooney
Sean D. Mooney University of Washington
Alfonso Valencia
Alfonso Valencia Barcelona Supercomputing Center
Silvio C. E. Tosatto
Silvio C. E. Tosatto University of Padua

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Expanding your expertise in Engineering and Technology can open up diverse career options, especially when supplemented with online degrees tailored to today’s industry needs. Many students combine technical backgrounds with skills in management, entrepreneurship, or real estate to boost their career prospects and leadership potential.

Those interested in business innovation may explore the best mba for entrepreneurship programs available online. These degrees help engineers transform innovative ideas into viable businesses by equipping them with vital business and leadership skills.

For professionals seeking accelerated advancement, a 1 year online mba no gmat option offers flexibility and speed, allowing students to grow their management skills without traditional testing barriers.

Managing complex engineering projects is also easier with credentials from a project management online degree. This pathway builds expertise in managing teams, budgets, and deadlines that are crucial in tech-driven industries.

If you’re interested in property development or infrastructure, a real estate degree online can complement your technical foundation and prepare you for specialized roles at the intersection of technology and real estate markets.

Best Scientists Citing Rita Casadio

Trending Scientists

Recently Published Articles