World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
7032
World Ranking
7648
National Ranking
242

Alok Sharma 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 Alok Sharma 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: 150 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Alok Sharma 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 Alok Sharma 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: 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.

Overview

Alok Sharma is affiliated with Griffith University in Australia and has made contributions primarily in the field of Biochemistry, Genetics and Molecular Biology. Their research spans several subfields including Molecular Biology, Cognitive Neuroscience, Pharmacology, Artificial Intelligence, and Complementary and Alternative Medicine.

Their work focuses on a range of topics, notably:

  • Machine Learning in Bioinformatics
  • RNA and protein synthesis mechanisms
  • Protein Structure and Dynamics
  • EEG and Brain-Computer Interfaces
  • Bioinformatics and Genomic Networks
  • Single-cell and spatial transcriptomics
  • Gene expression and cancer classification

Recent papers authored or co-authored by Alok Sharma include:

  • Advances in AI and machine learning for predictive medicine (2024), Journal of Human Genetics
  • DeepFeature: feature selection in nonimage data using convolutional neural network (2021), Briefings in Bioinformatics

Other notable relevant papers in their collaborative network, though authored by colleagues, are:

  • Critical assessment of protein intrinsic disorder prediction (2021), Nature Methods
  • ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides (2021), Scientific Reports
  • Prognosis prediction model for conversion from mild cognitive impairment to Alzheimer's disease created by integrative analysis of multi-omics data (2020), Alzheimer's Research & Therapy

Alok Sharma frequently collaborates with a group of researchers including:

  • Tatsuhiko Tsunoda
  • Abdollah Dehzangi
  • Swakkhar Shatabda
  • Keith A. Boroevich
  • Artem Lysenko

Their publications are most commonly found in the following venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Scientific Reports
  • Briefings in Bioinformatics
  • Genes
  • Current Traditional Medicine

Alok Sharma contributes substantially to integrating computational methods such as deep learning and convolutional neural networks with biological data analysis. Their work includes using AI techniques for predictive medicine and bioinformatics feature selection, reflecting an interdisciplinary approach that bridges biological science and artificial intelligence.

Best Publications

  • Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

    Rhys Heffernan;Kuldip Paliwal;James Lyons;Abdollah Dehzangi

  • DeepInsight: a methodology to transform a non - image data to an image for convolution neural network architecture

    Alokanand Sharma;Edwin Vans;Edwin Vans;Daichi Shigemizu;Keith A. Boroevich

  • Linear discriminant analysis for the small sample size problem: an overview

    Alok Sharma;Alok Sharma;Kuldip Kumar Paliwal

  • Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC

    Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma;James Lyons

  • Fast principal component analysis using fixed-point algorithm

    Alok Sharma;Kuldip K. Paliwal

  • A Top-r Feature Selection Algorithm for Microarray Gene Expression Data

    Alok Sharma;Seiya Imoto;Satoru Miyano

  • SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks

    Yuedong Yang;Rhys Heffernan;Kuldip Paliwal;James Lyons

  • Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

    James G. Lyons;Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma

  • A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition.

    Alok Sharma;James Lyons;Abdollah Dehzangi;Abdollah Dehzangi;Kuldip Kumar Paliwal

  • An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information

    Shiu Kumar;Shiu Kumar;Alok Sharma;Tatsuhiko Tsunoda

  • Autologous Bone Marrow Mononuclear Cell Therapy for Autism: An Open Label Proof of Concept Study

    Alok Sharma;Nandini Gokulchandran;Hemangi Sane;Anjana Nagrajan

  • A Deep Learning Approach for Motor Imagery EEG Signal Classification

    Shiu Kumar;Alok Sharma;Kabir Mamun;Tatsuhiko Tsunoda

  • Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins

    Rhys Heffernan;Abdollah Dehzangi;Abdollah Dehzangi;James G. Lyons;Kuldip K. Paliwal

  • Cancer classification by gradient LDA technique using microarray gene expression data

    Alok Sharma;Kuldip K. Paliwal

  • Brain wave classification using long short-term memory network based OPTICAL predictor.

    Shiu Kumar;Alok Sharma;Tatsuhiko Tsunoda

  • Intrusion detection using text processing techniques with a kernel based similarity measure

    Alok Sharma;Arun K. Pujari;Kuldip K. Paliwal

  • PyFeat: A Python-based Effective Feature Generation Tool for DNA, RNA, and Protein Sequences.

    Rafsanjani Muhammod;Sajid Ahmed;Dewan M. Farid;Swakkhar Shatabda

  • Predict Gram-Positive and Gram-Negative Subcellular Localization via Incorporating Evolutionary Information and Physicochemical Features Into Chou's General PseAAC

    Ronesh Sharma;Abdollah Dehzangi;James Lyons;Kuldip Paliwal

  • Principal component analysis using QR decomposition

    Alok Sharma;Alok Sharma;Kuldip Kumar Paliwal;Seiya Imoto;Satoru Miyano

  • A feature selection method using improved regularized linear discriminant analysis

    Alok Sharma;Kuldip K. Paliwal;Seiya Imoto;Satoru Miyano

  • Null space based feature selection method for gene expression data

    Alok Sharma;Alok Sharma;Seiya Imoto;Satoru Miyano;Vandana Sharma

Frequent Co-Authors

Kuldip K. Paliwal
Kuldip K. Paliwal Griffith University
Abdollah Dehzangi
Abdollah Dehzangi Rutgers, The State University of New Jersey
Tatsuhiko Tsunoda
Tatsuhiko Tsunoda University of Tokyo
Abdul Sattar
Abdul Sattar Griffith University
Mamannamana Vijayan
Mamannamana Vijayan Indian Institute of Science
Satoru Miyano
Satoru Miyano Tokyo Medical and Dental University
Victor Wray
Victor Wray Heinrich Heine University Düsseldorf
Peter Henklein
Peter Henklein Humboldt-Universität zu Berlin
Ulrich S. Schubert
Ulrich S. Schubert Friedrich Schiller University Jena
Yaoqi Zhou
Yaoqi Zhou Griffith University

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