Biomedical articles

(2024)

1. https://doi.org/10.18483/ijSci.2805
2. https://doi.org/10.9790/2834-1905010107
3. https://doi.org/10.1002/open.202400091
4. https://doi.org/10.1016/j.canlet.2024.217159
5. https://doi.org/10.1016/j.heliyon.2024.e36041
6. https://doi.org/10.1016/j.ijbiomac.2024.136940
7. https://doi.org/10.1016/j.jmb.2024.168717
8. https://doi.org/10.1016/j.jmgm.2024.108835
9. https://doi.org/10.1016/j.ymeth.2024.08.005
10. https://doi.org/10.1080/15476286.2023.2257471
11. https://doi.org/10.1093/bib/bbae030
12. https://doi.org/10.1093/bioadv/vbae173
13. https://doi.org/10.1371/journal.pcbi.1012399
14. https://doi.org/10.3389/fgene.2024.1469011
15. https://doi.org/10.3390/md22110501
16. https://doi.org/10.54692/ijeci.2023.0703160
17. https://doi:10.1152/ajpcell.00648.2023
18. https://doi.org/10.2174/0115748936287244240117065325
19. https://doi.org/10.1186/s12859-024-05738-1
20. https://doi.org/10.3390/biom14040423
21. https://doi.org/10.1038/s41598-024-57457-5
22. https://doi.org/10.1016/j.ymeth.2024.05.004
23. https://doi.org/10.1016/j.compbiomed.2024.108466
24. https://doi.org/10.3390/pr12061129
25. https://doi.org/10.1371/journal.pone.0305406
26. https://doi.org/10.3390/biom14070767
27. https://doi.org/10.1016/j.jmgm.2024.108835
28. https://doi.org/10.3390/pharmaceutics16080997
29. https://doi.org/10.1016/j.jmb.2024.168717
30. https://doi.org/10.1016/j.ab.2024.115495
31. https://doi.org/10.1093/bib/bbae169
32. https://doi.org/10.1101/2023.08.03.551768
33. https://doi.org/10.1016/j.compbiomed.2023.107848
34. https://doi.org/10.1016/j.omtn.2024.102192
35. https://doi.org/10.3390/ijms25094911
36. https://doi.org/10.1101/2023.12.14.571762
37. https://doi.org/10.1016/j.ymeth.2024.06.012
38. https://link.springer.com/article/10.1007/s10930-024-10219-8
39. https://doi.org/10.1109/ICEENG58856.2024.10566462
40. https://doi.org/10.1007/s00500-023-09577-9
41. https://doi.org/10.1186/s12864-024-10077-9
42. https://doi.org/10.1080/15476286.2024.2315384
43. https://doi.org/10.1016/j.compbiomed.2024.108166
44. https://doi.org/10.3934/mbe.2024169
45. https://doi.org/10.1093/bioinformatics/btae004
46. https://doi.org/10.18483/ijSci.2743
47. https://doi.org/10.2174/0115748936287244240117065325
48. https://doi.org/10.3390/biophysica4010005
49. https://doi.org/10.2174/0115748936287244240117065325
50. https://doi.org/10.1007/s10910-023-01568-3

(2023)

1. https://doi.org/10.3233/JCM-226872
2. https://doi.org/10.3389/fgene.2023.1334132
3. https://doi.org/10.1002/agm2.12274
4. https://doi.org/10.36371/port.2023.4.8
5. https://doi.org/10.1016/j.compbiolchem.2023.107974
6. https://doi.org/10.1101/2023.09.01.555875
7. https://doi.org/10.1038/s41598-023-45461-0
8. https://doi.org/10.1186/s12864-023-09796-2
9. https://doi.org/10.1186/s13040-023-00348-8
10. https://doi.org/10.1016/j.biosystems.2023.105094
11. https://doi:10.3389/fmicb.2023.1277099
12. https://doi:10.1088/1742-6596/2432/1/012022
13. https://doi:10.3934/mbe.2024012
14. https://doi:10.3390/molecules28248097
15. https://10.3389/fgene.2023.1334132
16. https://10.3389/fimmu.2023.1267755
17. https://doi.org/10.1016/j.dsp.2023.104137
18. https://doi.org/10.1021/acs.jcim.3c00366
19. https://doi.org/10.1007/s12539-023-00572-0
20. https://doi.org/10.3390/ijms24097878
21. https://doi.org/10.1016/j.omtn.2023.04.015
22. https://doi.org/10.1186/s12859-023-05232-0
23. https://doi.org/10.1186/s11658-023-00427-y
24. https://doi.org/10.1016/j.omtn.2023.01.014
25. https://doi.org/10.1016/j.bej.2023.108990
26. https://doi.org/10.1016/j.compbiomed.2023.107030
27. https://doi.org/10.3390/biomimetics8020218
28. https://doi.org/10.1093/nar/gkad404
29. https://doi.org/10.1016/j.bspc.2022.104362
30. https://doi.org/10.1016/j.omtn.2023.02.026
31. https://doi.org/10.3390/app13053326
32. https://doi.org/10.3390/ijms23158314
33. https://doi.org/10.3390/biomedicines11020237
34. https://doi.org/10.1101/2023.08.03.551768
35. https://doi.org/10.1007/s12064-023-00402-3
36. https://doi.org/10.1371/journal.pone.0290845
37. https://doi.org/10.20944/preprints202308.0123.v1
38. https://doi.org/10.1016/j.ijbiomac.2023.123180
39. https://doi.org/10.1016/j.bspc.2022.104362

(2022)

1. https://doi.org/10.3390/molecules27217280
2. https://doi.org/10.1016/j.csbj.2022.11.026
3. https://doi.org/10.1101/2022.12.07.519510
4. https://doi.org/10.1093/bib/bbac546
5. https://doi.org/10.1093/bib/bbac514
6. https://doi.org/10.1080/13102818.2022.2122871
7. https://doi.org/10.1109/ATSIP55956.2022.9805882
8. https://doi.org/10.1007/978-3-031-11713-8_24
9. https://doi.org/10.1016/j.bspc.2022.104362
10. https://doi.org/10.3389/fmicb.2022.1061122
11. https://doi.org/10.1093/bib/bbac467
12. https://doi.org/10.3389/fmicb.2022.1042127
13. https://doi.org/10.3390/app122010216
14. https://doi.org/10.21203/rs.3.rs-1997163/v1
15. https://doi.org/10.22369/issn.2153-4136/9/2/4
16. https://doi.org/10.1093/bioinformatics/btac671
17. https://doi.org/10.31083/j.fbl2709269
18. https://doi.org/10.17341/gazimmfd.1022624
19. https://doi.org/10.3389/fmolb.2022.898627
20. https://doi.org/10.3390/ijms231911026
21. https://doi.org/10.32604/biocell.2022.016655
22. https://doi.org/10.3934/mbe.2022644
23. https://10.1109/ACCESS.2020.3020592
24. https://doi.org/10.3390/app122010216
25. https://doi.org/10.3390/molecules27217280
26. https://doi.org/10.21203/rs.3.rs-1223538/v1
27. https://doi.org/10.1007/978-981-15-7253-1_1
28. https://doi.org/10.1016/j.matpr.2022.02.394
29. https://doi.org/10.1016/j.ymeth.2022.03.001
30. https://doi.org/10.1007/s00521-022-07121-8
31. https://doi.org/10.3390/ijms23063044
32. https://doi.org/10.1093/bib/bbac082
33. https://doi.org/10.1093/bib/bbab434
34. https://doi.org/10.1016/j.ygeno.2022.110384
35. https://doi.org/10.1186/s43088-022-00216-0
36. https://doi.org/10.1093/nar/gkac351
37. https://doi.org/10.3389/fphar.2022.831791
38. https://doi.org/10.3390/molecules27092626
39. https://doi.org/10.1371/journal.ppat.1010345
40. https://doi.org/10.3390/genes13040677
41. https://doi.org/10.1016/j.ymeth.2022.04.003
42. https://doi.org/10.37394/23208.2022.19.11
43. https://doi.org/10.1093/bfgp/elab045
44. https://doi.org/10.4018/978-1-7998-5351-0.ch043
45. https://doi.org/10.3390/app12031344
46. https://doi.org/10.1371/journal.pcbi.1009798
47. https://doi.org/10.1007/s12539-021-00500-0
48. https://doi.org/10.33774/chemrxiv-2021-39cd6-v2
49. https://doi.org/10.1016/j.jbi.2022.104016
50. https://doi.org/10.46300/91011.2022.16.16
51. https://doi.org/10.1093/bioinformatics/btab611
52. https://doi.org/10.1177/17483026211031163
53. https://doi.org/10.1016/j.bspc.2021.103317
54. https://doi.org/10.1002/open.202100248
55. https://doi.org/10.1101/2022.02.08.479502
56. https://doi.org/10.1038/s41598-022-14127-8
57. https://doi.org/10.1016/j.bspc.2022.103909
58. https://doi.org/10.21203/rs.3.rs-1743456/v1
59. https://doi.org/10.3390/ijms23158314
60. https://doi.org/10.1016/j.chemolab.2022.104622
61. https://www.researchgate.net/publication/362070879
62. https://doi.org/10.1016/j.ins.2022.05.060
63. https://doi.org/10.1186/s12859-022-04821-9
64. https://doi.org/10.1016/j.compbiolchem.2022.107732
65. https://doi.org/10.3390/e24070978
66. https://doi.org/10.3390/molecules27092626
67. https://doi.org/10.3390/ijms23158221
68. https://doi.org/10.1371/journal.ppat.1010345
69. https://doi.org/10.1128/mbio.00076-22
70. https://doi.org/10.31083/j.fbl2705152
71. https://doi.org/10.1002/open.202100248
72. https://doi.org/10.37394/23208.2022.19.11
73. https://doi.org/10.3390/genes13040677

(2021)

1. https://doi.org/10.3390/vaccines9070751
2. https://doi.org/10.3390/ncrna7040077
3. https://doi.org/10.3390/a14100283
4. https://doi.org/10.1093/bib/bbaa401
5. https://doi.org/10.1177/17483026211031163
6. https://doi.org/10.46300/91011.2021.15.7
7. https://doi.org/10.1007/s12539-020-00405-4
8. https://doi.org/10.18483/ijSci.2433
9. https://doi.org/10.3390/genes12020296
10. https://doi.org/10.1093/nar/gkab122
11. https://doi.org/10.3969/j.issn.1673-629X.2021.03.026
12. https://doi.org/10.1016/j.ymthe.2021.04.004
13. https://doi.org/10.1080/15476286.2021.1898160
14. https://doi.org/10.1109/TNB.2021.3077710
15. https://doi.org/10.18483/ijSci.2459
16. https://doi.org/10.3389/fcell.2021.664669
17. https://doi.org/10.7717/peerj.11456
18. https://doi.org/10.1002/prot.26149
19. https://doi.org/10.1155/2021/5515342
20. https://doi.org/10.1088/1742-6596/1921/1/012042
21. https://doi.org/10.3389/fgene.2021.670852
22. https://doi.org/10.18483/ijSci.2482
23. https://doi.org/10.1007/s12539-020-00405-4
24. https://doi.org/10.3906/elk-2003-116
25. https://doi.org/10.1371/journal.pone.0244948.g002
26. https://doi.org/10.1016/j.ymeth.2021.01.007
27. https://doi.org/10.1016/j.ygeno.2020.09.054
28. https://doi.org/10.1093/bib/bbab011
29. https://doi.org/10.1038/s41598-021-85856-5
30. https://doi.org/10.1142/S0219720021500049
31. https://doi.org/10.1155/2021/9969751
32. https://doi.org/10.1007/s11103-021-01204-1
33. https://doi.org/0.1093/bioinformatics/btaa972
34. https://doi.org/10.1016/j.bspc.2021.103317
35. https://doi.org/10.1016/j.imlet.2021.11.003
36. https://doi.org/10.1093/bib/bbab434
37. https://doi.org/10.1016/j.csbj.2021.09.025
38. https://doi.org/10.1186/s43042-021-00192-7
39. https://doi.org/10.1016/j.ygeno.2021.07.004
40. https://doi.org/10.1007/978-3-030-79311-1_14
41. https://doi.org/10.1093/bioinformatics/btab611
42. https://doi.org/10.3390/ijms22179106
43. https://doi.org/10.3390/app11167731
44. https://doi.org/10.1016/j.compbiomed.2021.104650
45. https://doi.org/10.1016/j.bspc.2021.102915
46. https://doi.org/10.18483/ijSci.2495
47. https://doi.org/10.3390/ijms22147361
48. https://doi.org/10.1016/j.heliyon.2021.e07933
49. https://doi.org/10.1128/mSphere.00216-21
50. https://doi.org/10.3390/ijms22147361

(2020)

1. https://doi.org/10.1186/s12864-020-07166-w
2. https://doi.org/10.1038/s41598-020-77824-2
3. https://doi.org/10.1016/j.csbj.2020.11.030
4. https://doi.org/10.1007/s12539-020-00399-z
5. https://doi.org/10.1155/2020/8852258
6. https://doi.org/10.1007/978-1-4939-7717-8_13
7. https://doi.org/10.18483/ijSci.2390
8. https://doi.org/10.1016/j.jbi.2020.103555
9. https://doi.org/10.1016/j.omtn.2020.09.010
10. https://doi.org/10.1016/j.csbj.2020.09.001
11. https://doi.org/10.1093/bib/bbaa202
12. https://doi.org/10.3389/fgene.2020.00090
13. https://doi.org/10.1016/j.omtn.2019.11.014
14. https://doi.org/10.1016/j.omtn.2020.06.004
15. https://doi.org/10.1109/ACCESS.2020.2991477
16. https://doi.org/10.1093/bib/bbaa170
17. https://doi.org/10.1002/cta.2838
18. https://doi.org/10.1093/bib/bbaa124
19. https://doi.org/10.1080/15257770.2020.1780442
20. https://doi.org/10.1093/bib/bbaa099
21. https://doi.org/10.1101/2020.06.08.140368
22. https://doi.org/10.1016/j.omtn.2020.06.004
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24. https://doi.org/10.1093/bib/bbaa304
25. https://doi.org/10.1016/j.ygeno.2020.09.054
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(1976-2019)

1. An Integrated-OFFT Model for the Prediction of Protein Secondary Structure Class.
   Panda B, Majhi B, Thakur A.
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   Albalawi F, Chahid A, Guo X, Albaradei S, Magana-Mora A, Jankovic BR, Uludag M, Van Neste C, Essack M, Laleg-Kirati TM, Bajic VB.
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   Liu B, Gao X, Zhang H.
   Nucleic Acids Res. 2019;47(20):e127. doi: 10.1093/nar/gkz740.
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   Hao-Tian Wang, Fu-Hui Xiao, Gong-Hua Li, Qing-Peng Kong
   Epigenetics Chromatin. 2020; 13: 8. doi: 10.1186/s13072-020-00330-2
6. 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-methylcytosine Sites in the Mouse Genome.
   Manavalan B, Basith S, Shin TH, Lee DY, Wei L, Lee G
   Cells 2019;8(11):1332. doi: 10.3390/cells8111332.
7. AggreRATE-Pred: A mathematical model for the prediction of change in aggregation rate upon point mutation.
   Rawat P, Prabakaran R, Kumar S, Gromiha MM
   Bioinformatics. 2019 Dec 1;35(23):4930-4937. doi: 10.1093/bioinformatics/btz408.
8. Iterative feature representations improve N4-methylcytosine site prediction.
   Wei L, Su R, Luan S, Liao Z, Manavalan B, Zou Q, Shi X
   Nucleosides Nucleotides Nucleic Acids. 2019;38(5):321-337. doi: 10.1080/15257770.2018.1536270.
9. Visual representation of DNA sequences for exon detection using non-parametric spectralestimation techniques.
   Dessouky AM, Taha TE, Dessouky MM, Eltholth AA, Hassan E, Abd El-Samie FE
   Sci Rep. 2019 Feb 15;9(1):2159. doi: 10.1038/s41598-018-38197-9.
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    Kouchaki S, Tapinos A, Robertson DL
    Viruses. 2019 Apr 26;11(5). pii: E394. doi: 10.3390/v11050394
11. The Utility of Data Transformation for Alignment, De Novo Assembly and Classification of Short Read Virus Sequences.
    Tapinos A, Constantinides B, Phan MVT, Kouchaki S, Cotten M, Robertson DL.
    Int J Mol Sci. 2019 Nov 11;20(22). pii: E5640. doi: 10.3390/ijms20225640.
12. Novel Descriptors and Digital Signal Processing-Based Method for Protein Sequence Activity Relationship Study.
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    Mol Ther Nucleic Acids. 2019 Nov 21;19:293-303. doi: 10.1016/j.omtn.2019.11.014.
13. Is There Any Sequence Feature in the RNa Pseudouridine Modification Prediction Problem?
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    Int J Biol Macromol. 2019 Dec 2. pii: S0141-8130(19)38547-2. doi: 10.1016/j.ijbiomac.2019.12.009.
14. i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome.
    Hasan MM, Manavalan B, Khatun MS, Kurata H
    Mol Ther Nucleic Acids. 2019 Jun 7;16:733-744. doi: 10.1016/j.omtn.2019.04.019.
15. Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation.
    Manavalan B, Basith S, Shin TH, Wei L, Lee G
    Curr Comput Aided Drug Des. 2019;15(1):45-54. doi:10.2174/1573409914666180828105228.
16. An Integrated-OFFT Model for the Prediction of Protein Secondary Structure Class.
    Panda B, Majhi B, Thakur A
    Comput Struct Biotechnol J. 2019 Mar 19;17:406-414. doi: 10.1016/j.csbj.2019.03.007.
17. A degeneration-reducing criterion for optimal digital mapping of genetic codes.
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    Bioinform Biol Insights. 2019 Jun 4;13:1177932219850172. doi: 10.1177/1177932219850172.
18. Time-Frequency Approach Appllied to finding Interaction Region in Pathogenic Proteins.
    Arenas AF, Arango-Plaza N, Arenas JC, Salcedo GE
    Bioinformatics. 2019 Apr 1;35(7):1125-1132. doi: 10.1093/bioinformatics/bty752.
19. DeepGSR: an optimized deep-learning structure for the recognition of genomic signals and regions.
    Kalkatawi M, Magana-Mora A, Jankovic B, Bajic VB
    Brief Bioinform. 2019 Apr 24. pii: bbz041. doi: 10.1093/bioinformatics/bty752.
20. iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.
    Chen Z, Zhao P, Li F, Marquez-Lago TT, Leier A, Revote J, Zhu Y, Powell DR, Akutsu T, Webb GI, Chou KC, Smith AI, Daly RJ, Li J, Song J
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21. ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels.
    Randhawa GS, Hill KA, Kari L
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22. Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR).
    Sencanski M, Glisic S, Šnajder M, Veljkovic N, Poklar Ulrih N, Mavri J, Vrecl M.
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23. Evolution of H5-Type Avian Influenza A Virus Towards Mammalian Tropism in Egypt, 2014 to 2015.
    Mahmoud SH, Mostafa A, El-Shesheny R, Seddik MZ, Khalafalla G, Shehata M, Kandeil A, Pleschka S, Kayali G, Webby R, Veljkovic V, Ali MA.
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