Downloads provided by UsageCountsSoftware used in "Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model"
Garcia, David A; Fettweis, Gregory; Presman, Diego M; Paakinaho, Ville; Jarzynski, Christopher; Upadhyaya, Arpita; Hager, Gordon L;
Software used in "Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model"
This contains single-molecule tracking and dwell time analysis software and example datasets used in the paper: "Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model." Nucleic acids research 49, no. 12 (2021): 6605-6620. The zip file contains: MatlabTrack_v6 – Single-molecule tracking program Analysis_scripts – MATLAB scripts for estimating photobleaching rate and computing photobleaching-corrected survival probability distributions Sample_Data – Example H2B and transcription factor (TF) data User manual User manual can be found in the source publication. Link to the original GitHub upload: https://github.com/davidalejogarcia/PL_HagerLab License GNU GENERAL PUBLIC LICENSE
- National Cancer Institute United States
- University of Buenos Aires Argentina
- National Scientific and Technical Research Council Argentina
- National Institutes of Health United States
- University of Maryland, College Park United States
Single-molecule tracking, transcription factor dynamics, power-law
Single-molecule tracking, transcription factor dynamics, power-law
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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