| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data
|
Pemberton-Ross, Peter J.
|
|
2015
|
85 |
C |
p. 62-74
|
artikel
|
| 2 |
Bayesian inference of reaction kinetics from single-cell recordings across a heterogeneous cell population
|
Bronstein, L.
|
|
2015
|
85 |
C |
p. 22-35
|
artikel
|
| 3 |
CAST: An automated segmentation and tracking tool for the analysis of transcriptional kinetics from single-cell time-lapse recordings
|
Blanchoud, Simon
|
|
2015
|
85 |
C |
p. 3-11
|
artikel
|
| 4 |
Computational assignment of cell-cycle stage from single-cell transcriptome data
|
Scialdone, Antonio
|
|
2015
|
85 |
C |
p. 54-61
|
artikel
|
| 5 |
Computer vision for image-based transcriptomics
|
Stoeger, Thomas
|
|
2015
|
85 |
C |
p. 44-53
|
artikel
|
| 6 |
Cover 1
|
|
|
2015
|
85 |
C |
p. OFC
|
artikel
|
| 7 |
Editorial Board
|
|
|
2015
|
85 |
C |
p. IFC
|
artikel
|
| 8 |
Exploiting the multiplexing capabilities of tandem mass tags for high-throughput estimation of cellular protein abundances by mass spectrometry
|
Ahrné, Erik
|
|
2015
|
85 |
C |
p. 100-107
|
artikel
|
| 9 |
Inferring gene expression regulatory networks from high-throughput measurements
|
Zavolan, Mihaela
|
|
2015
|
85 |
C |
p. 1-2
|
artikel
|
| 10 |
Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics
|
Munsky, Brian
|
|
2015
|
85 |
C |
p. 12-21
|
artikel
|
| 11 |
Quantification of co-transcriptional splicing from RNA-Seq data
|
Herzel, Lydia
|
|
2015
|
85 |
C |
p. 36-43
|
artikel
|
| 12 |
Quantifying the strength of miRNA–target interactions
|
Breda, Jeremie
|
|
2015
|
85 |
C |
p. 90-99
|
artikel
|
| 13 |
Transcriptome-wide measurement of ribosomal occupancy by ribosome profiling
|
Aeschimann, Florian
|
|
2015
|
85 |
C |
p. 75-89
|
artikel
|
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