قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| تحليل Hi-C× | سرعة الحمض النووي الريبوزي (RNA Velocity)× | |
|---|---|---|
| المجال | علم الوراثة | علم الوراثة |
| العائلة | Process / pipeline | Process / pipeline |
| سنة النشأة≠ | 2009 | 2018 |
| صاحب الطريقة≠ | Erez Lieberman-Aiden & Job Dekker | Gioele La Manno & Pavel Soldatov |
| النوع≠ | Chromatin interaction method | Trajectory inference method |
| المصدر التأسيسي≠ | Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., & Dekker, J. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326(5950), 289–293. DOI ↗ | La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., & Merad, M. (2018). RNA velocity of single cells. Nature, 560(7737), 494–498. DOI ↗ |
| الأسماء البديلة | Chromosome conformation capture, 3D genome, Chromatin contact mapping | Velocity analysis, Transcriptomic velocity, Cell fate prediction |
| ذات صلة | 2 | 2 |
| الملخص≠ | Hi-C (High-Chromosome Conformation Capture) is a technique and associated computational methods for mapping the 3D architecture of the genome within cells. Developed by Lieberman-Aiden and Dekker in 2009, Hi-C identifies physical interactions between genomic regions that may be distant in linear sequence but spatially proximal in 3D nuclear space. Hi-C analysis has revealed fundamental principles of genome organization, including the existence of topologically associating domains (TADs), and provides insights into how 3D structure regulates gene expression and DNA replication. | RNA velocity is a computational method that infers the future developmental state of individual cells from single-cell RNA-sequencing data. Developed by La Manno and colleagues in 2018, RNA velocity analysis measures the direction and pace of cell state transitions by analyzing the ratio of unspliced to spliced mRNA transcripts within individual cells. This enables prediction of cell trajectories and differentiation pathways without requiring temporal sampling or manipulation, providing unique insights into cell fate decisions during development and disease. |
| ScholarGateمجموعة البيانات ↗ |
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