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2025

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Rising Stars

D-Index
34
Citations
2894
World Ranking
901
National Ranking
15

Computer Science

D-Index
41
Citations
3474
World Ranking
9003
National Ranking
12

Yaser Daanial Khan 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 Yaser Daanial Khan 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: 94 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Yaser Daanial Khan 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 Yaser Daanial Khan 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Yaser Daanial Khan is affiliated with the University of Management and Technology in Pakistan. Their primary research field is Biochemistry, Genetics and Molecular Biology, with a particular focus on Molecular Biology. Their work also touches on Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Epidemiology, and Cancer Research.

The scientist's research covers a range of topics related to bioinformatics and molecular science. Major themes include:

  • Machine Learning in Bioinformatics
  • RNA and protein synthesis mechanisms
  • Genomics and Phylogenetic Studies
  • Vaccines and immunoinformatics approaches
  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Genetics, Bioinformatics, and Biomedical Research

Yaser Daanial Khan has published extensively in multiple scientific venues. Notable publication outlets where they have multiple papers include:

  • Scientific Reports (7 publications)
  • Digital Health (5 publications)
  • Current Bioinformatics (4 publications)
  • Analytical Biochemistry (3 publications)
  • IEEE Access (3 publications)

Among recent publications are the following:

  • "Evaluating machine learning methodologies for identification of cancer driver genes," 2021, Scientific Reports
  • "Identification of 4-carboxyglutamate residue sites based on position based statistical feature and multiple classification," 2020, Scientific Reports
  • "StackACPred: Prediction of anticancer peptides by integrating optimized multiple feature descriptors with stacked ensemble approach," 2021, Chemometrics and Intelligent Laboratory Systems
  • "Optimization of serine phosphorylation prediction in proteins by comparing human engineered features and deep representations," 2020, Analytical Biochemistry
  • "Insights into Machine Learning-based Approaches for Virtual Screening in Drug Discovery: Existing Strategies and Streamlining Through FP-CADD," 2020, Current Drug Discovery Technologies

The scientist collaborates frequently with several researchers in their domain. Frequent coauthors include:

  • Tamim Alkhalifah
  • Fahad Alturise
  • Waqar Hussain
  • Sharaf J. Malebary
  • Nouman Rasool

Best Publications

  • SPrenylC-PseAAC: A sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins

    Waqar Hussain;Yaser Daanial Khan;Nouman Rasool;Sher Afzal Khan

  • SPalmitoylC-PseAAC: A sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-palmitoylation sites in proteins.

    Waqar Hussain;Yaser Daanial Khan;Nouman Rasool;Sher Afzal Khan

  • iPhosT-PseAAC: Identify phosphothreonine sites by incorporating sequence statistical moments into PseAAC.

    Yaser Daanial Khan;Nouman Rasool;Waqar Hussain;Sher Afzal Khan

  • Prediction of N-linked glycosylation sites using position relative features and statistical moments.

    Muhammad Aizaz Akmal;Nouman Rasool;Yaser Daanial Khan

  • Iris recognition using image moments and k-means algorithm.

    Yaser Daanial Khan;Sher Afzal Khan;Farooq Ahmad;Saeed Islam

  • iPhosY-PseAAC: identify phosphotyrosine sites by incorporating sequence statistical moments into PseAAC.

    Yaser Daanial Khan;Nouman Rasool;Waqar Hussain;Sher Afzal Khan

  • A Novel Modeling in Mathematical Biology for Classification of Signal Peptides

    Asma Ehsan;Khalid Mahmood;Yaser Daanial Khan;Sher Afzal Khan

  • iPhosH-PseAAC: Identify Phosphohistidine Sites in Proteins by Blending Statistical Moments and Position Relative Features According to the Chou's 5-Step Rule and General Pseudo Amino Acid Composition

    Muhammad Awais;Waqar Hussain;Yaser Daanial Khan;Nouman Rasool

  • A Treatise to Computational Approaches Towards Prediction of Membrane Protein and Its Subtypes

    Ahmad Hassan Butt;Nouman Rasool;Yaser Daanial Khan

  • Predicting membrane proteins and their types by extracting various sequence features into Chou’s general PseAAC

    Ahmad Hassan Butt;Nouman Rasool;Yaser Daanial Khan

  • pNitro-Tyr-PseAAC: Predict Nitrotyrosine Sites in Proteins by Incorporating Five Features into Chou’s General PseAAC

    Ahmad W Ghauri;Yaser D Khan;Nouman Rasool;Sher A Khan

  • StackACPred: Prediction of anticancer peptides by integrating optimized multiple feature descriptors with stacked ensemble approach

    Muhammad Arif;Muhammad Arif;Saeed Ahmed;Fang Ge;Muhammad Kabir

  • A Neuro-Cognitive Approach for Iris Recognition Using Back Propagation

    Yaser Daanial Khan;Farooq Ahmad;Muhammad Waqas Anwar

  • A Prediction Model for Membrane Proteins Using Moments Based Features

    Ahmad Hassan Butt;Sher Afzal Khan;Hamza Jamil;Nouman Rasool

  • Evaluating machine learning methodologies for identification of cancer driver genes.

    Sharaf J. Malebary;Yaser Daanial Khan

  • Situation recognition using image moments and recurrent neural networks

    Yaser Daanial Khan;Farooq Ahmed;Sher Afzal Khan

  • iCrotoK-PseAAC: Identify lysine crotonylation sites by blending position relative statistical features according to the Chou's 5-step rule

    Sharaf Jameel Malebary;Muhammad Safi ur Rehman;Yaser Daanial Khan

  • Identification of 4-carboxyglutamate residue sites based on position based statistical feature and multiple classification

    Asghar Ali Shah;Yaser Daanial Khan

  • Prediction of antioxidant proteins by incorporating statistical moments based features into Chou's PseAAC.

    Ahmad Hassan Butt;Nouman Rasool;Yaser Daanial Khan

  • iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou's 5-steps Rule and Pseudo Components.

    Omar Barukab;Yaser Daanial Khan;Sher Afzal Khan;Kuo Chen Chou

  • iMethylK_pseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAAC via Chou's 5-steps Rule.

    Sarah Ilyas;Waqar Hussain;Adeel Ashraf;Yaser Daanial Khan

Frequent Co-Authors

Kuo-Chen Chou
Kuo-Chen Chou The Gordon Life Science Institute
Muhammad Farooq
Muhammad Farooq Sultan Qaboos University
Saeed Islam
Saeed Islam Abdul Wali Khan University Mardan
Daojing He
Daojing He East China Normal University
Dong-Jun Yu
Dong-Jun Yu Nanjing University of Science and Technology

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