| 1. |
- Thul, Peter J., et al.
(författare)
-
A subcellular map of the human proteome
- 2017
-
Ingår i: Science. - : American Association for the Advancement of Science. - 0036-8075 .- 1095-9203. ; 356:6340
-
Tidskriftsartikel (refereegranskat)abstract
- Resolving the spatial distribution of the human proteome at a subcellular level can greatly increase our understanding of human biology and disease. Here we present a comprehensive image-based map of subcellular protein distribution, the Cell Atlas, built by integrating transcriptomics and antibody-based immunofluorescence microscopy with validation by mass spectrometry. Mapping the in situ localization of 12,003 human proteins at a single-cell level to 30 subcellular structures enabled the definition of the proteomes of 13 major organelles. Exploration of the proteomes revealed single-cell variations in abundance or spatial distribution and localization of about half of the proteins to multiple compartments. This subcellular map can be used to refine existing protein-protein interaction networks and provides an important resource to deconvolute the highly complex architecture of the human cell.
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
- Danielsson, Frida, et al.
(författare)
-
RNA Deep Sequencing as a Tool for Selection of Cell Lines for Systematic Subcellular Localization of All Human Proteins
- 2013
-
Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 12:1, s. 231-239
-
Tidskriftsartikel (refereegranskat)abstract
- One of the major challenges of a chromosome-centric proteome project is to explore in a systematic manner the potential proteins identified from the chromosomal genome sequence, but not yet characterized on a protein level. Here, we describe the use of RNA deep sequencing to screen human cell lines for RNA profiles and to use this information to select cell lines suitable for characterization of the corresponding gene product. In this manner, the subcellular localization of proteins can be analyzed systematically using antibody-based confocal microscopy. We demonstrate the usefulness of selecting cell lines with high expression levels of RNA transcripts to increase the likelihood of high quality immunofluorescence staining and subsequent successful subcellular localization of the corresponding protein. The results show a path to combine transcriptomics with affinity proteomics to characterize the proteins in a gene- or chromosome-centric manner.
|
|
| 5. |
- Fagerberg, Linn, et al.
(författare)
-
Mapping the subcellular protein distribution in three human cell lines
- 2011
-
Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 10:8, s. 3766-3777
-
Tidskriftsartikel (refereegranskat)abstract
- The subcellular locations of proteins are closely related to their function and constitute an essential aspect for understanding the complex machinery of living cells. A systematic effort has been initiated to map the protein distribution in three functionally different cell lines with the aim to provide a subcellular localization index for at least one representative protein from all human protein-encoding genes. Here, we present the results of over 4,000 proteins mapped to 16 subcellular compartments. The results indicate a ubiquitous protein expression with a majority of the proteins found in all three cell lines and a large portion localized to two or more compartments. The inter-relationships between the subcellular compartments are visualized in a protein-compartment network based on all detected proteins. Hierarchical clustering was performed to determine how closely related the organelles are in terms of protein constituents and compare the proteins detected in each cell type. Our results show distinct organelle proteomes, well conserved across the cell types, and demonstrate that biochemically similar organelles are grouped together.
|
|
| 6. |
|
|
| 7. |
- Mahdessian, Diana, et al.
(författare)
-
Profiling the human cytoplasmic proteome.
- 2016
-
Ingår i: Molecular Biology of the Cell. - : AMER SOC CELL BIOLOGY. - 1059-1524 .- 1939-4586. ; 27
-
Tidskriftsartikel (refereegranskat)
|
|
| 8. |
- Ouyang, Wei, et al.
(författare)
-
Analysis of the Human Protein Atlas Image Classification competition
- 2019
-
Ingår i: Nature Methods. - : Springer Nature. - 1548-7091 .- 1548-7105. ; 16:12, s. 1254-
-
Tidskriftsartikel (refereegranskat)abstract
- Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition to identify deep learning solutions to solve this task. Challenges included training on highly imbalanced classes and predicting multiple labels per image. Over 3 months, 2,172 teams participated. Despite convergence on popular networks and training techniques, there was considerable variety among the solutions. Participants applied strategies for modifying neural networks and loss functions, augmenting data and using pretrained networks. The winning models far outperformed our previous effort at multi-label classification of protein localization patterns by similar to 20%. These models can be used as classifiers to annotate new images, feature extractors to measure pattern similarity or pretrained networks for a wide range of biological applications.
|
|
| 9. |
|
|
| 10. |
|
|
