INFOMATICS RESEARCH TOPICS AND MATERIALS
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INFOMATICS RESEARCH TOPICS AND MATERIALS
1. Comparative genomics of disease resistance genes in crops.
2. Analysis of functional non-coding RNA in the human genome.
3. Computational prediction of protein-protein interactions.
4. Metagenomics: Unraveling the microbial communities in the human gut.
5. Network-based approaches for understanding disease pathways.
6. Identification of potential drug targets using structural bioinformatics.
7. Analysis of single-cell RNA sequencing data for understanding cell heterogeneity.
8. Evolutionary analysis of regulatory elements in the human genome.
9. Computational prediction of microRNA targets.
10. Phylogenetic analysis of viral genomes.
11. Epigenomic profiling in cancer research.
12. Comparative analysis of gene expression in different tissues.
13. Functional annotation of unknown genes using bioinformatics.
14. Genomic analysis of antibiotic resistance in bacteria.
15. Drug repurposing through data mining of existing compounds.
16. Machine learning in protein structure prediction.
17. Personalized medicine and pharmacogenomics.
18. Analysis of alternative splicing in disease pathways.
19. Structural and functional analysis of membrane proteins.
20. Epitranscriptomics: RNA modifications and their functional implications.
21. Analysis of long non-coding RNA in cancer.
22. Genomic analysis of rare diseases.
23. Predicting transcription factor binding sites.
24. Quantitative trait loci (QTL) mapping in plant genetics.
25. Functional analysis of non-coding RNA in neurodegenerative diseases.
26. Comparative metagenomics of different environmental samples.
27. Computational tools for analyzing high-throughput sequencing data.
28. Structural analysis of RNA-protein interactions.
29. Drug design and virtual screening in infectious diseases.
30. Network-based drug repositioning for cancer therapy.
31. Analysis of host-pathogen interactions in infectious diseases.
32. Predictive modeling of RNA secondary structure.
33. Functional annotation of metagenomic data.
34. Integrative analysis of multi-omics data in cancer research.
35. Evolutionary genomics of hominins and modern humans.
36. Regulatory motifs and cis-regulatory elements in gene regulation.
37. Machine learning for predicting protein functions.
38. Computational approaches for predicting RNA editing events.
39. Analyzing microbiome diversity in health and disease.
40. Comparative analysis of mitochondrial genomes.
41. Predicting drug-drug interactions using bioinformatics.
42. Analysis of RNA splicing variants in neurological disorders.
43. Systems biology approaches in understanding complex diseases.
44. Structural prediction of RNA molecules.
45. Functional analysis of long non-coding RNA in development.
46. Bioinformatics tools for metaproteomics analysis.
47. Genomic variation and adaptation in natural populations.
48. Computational methods for identifying disease biomarkers.
49. Evolutionary analysis of transposable elements.
50. Metabolomics data analysis for biomarker discovery.
51. Structural bioinformatics of protein-ligand interactions.
52. Epigenetic modifications and their role in cancer progression.
53. Computational tools for analyzing RNA-seq data.
54. Microbiome and human health: Analyzing associations.
55. Genome-wide association studies (GWAS) in complex diseases.
56. Functional annotation of non-coding elements in the genome.
57. Analysis of chromatin conformation data in gene regulation.
58. Comparative genomics of extremophiles.
59. Drug resistance mechanisms in infectious diseases.
60. Network-based analysis of cancer signaling pathways.
61. Structural and functional analysis of RNA editing.
62. Computational methods for metagenomic assembly.
63. Prediction of post-translational modifications in proteins.
64. Evolutionary genomics of plant adaptation to climate change.
65. Integrated multi-omics analysis in precision medicine.
66. Comparative analysis of ancient DNA from archaeological samples.
67. Computational tools for identifying protein domains.
68. Epitranscriptomics in stem cell differentiation.
69. Analysis of transcription factor binding in enhancer regions.
70. Predictive modeling of protein stability and folding.
71. Functional analysis of circular RNAs in disease.
72. Pathway analysis and network inference in biological systems.
73. Structural prediction of non-coding RNA molecules.
74. Metabolomics in understanding metabolic diseases.
75. Genomic analysis of population genetics in non-model organisms.
76. Computational approaches for identifying gene fusions in cancer.
77. Epigenetic regulation of gene expression in development.
78. Analyzing post-transcriptional regulation in gene expression.
79. Functional annotation of non-coding RNAs in plant biology.
80. Comparative genomics of marine organisms.
81. Drug target prediction in neglected tropical diseases.
82. Network pharmacology for drug discovery.
83. Structural analysis of RNA modifications.
84. Integrative analysis of transcriptomics and proteomics data.
85. Comparative analysis of regulatory networks in different species.
86. Machine learning for predicting RNA-protein interactions.
87. Microbiome and its role in autoimmune diseases.
88. Genomic analysis of epigenetic changes in aging.
89. Predicting RNA folding and secondary structure.
90. Functional analysis of small RNAs in developmental processes.
91. Metagenomic data analysis in environmental microbiology.
92. Drug design for personalized medicine.
93. Regulatory network inference in plant stress responses.
94. Structural bioinformatics of membrane proteins.
95. Epitranscriptomic modifications and their role in stem cell biology.
96. Computational prediction of transcription factor binding motifs.
97. Functional annotation of long non-coding RNAs in cancer.
98. Comparative genomics of ancient crops.
99. Metabolomics profiling in precision medicine.
100. Analyzing the role of non-coding RNAs in immune responses.
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