The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
A Systems-Level Analysis of the Peripheral Nerve Intrinsic Axonal Growth Program
Open accessAbstract
SUMMARY The regenerative capacity of the injured CNS in adult mammals is severely limited, yet axons in the peripheral nervous system (PNS) regrow, albeit to a limited extent, after injury. We reasoned that coordinate regulation of gene expression in injured neurons involving multiple pathways was central to PNS regenerative capacity. To provide a framework for revealing pathways involved in PNS axon regrowth after injury, we applied a comprehensive systems biology approach, starting with gene expression profiling of dorsal root ganglia (DRGs) combined with multi-level bioinformatic analyses and experimental validation of network predictions. We used this rubric to identify a drug that accelerates DRG neurite outgrowth in vitro and optic nerve outgrowth in vivo by inducing elements of the identified network. The work provides a functional genomics foundation for understanding neural repair and proof of the power of such approaches in tackling complex problems in nervous system biology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Self-citationTakahashi, K., & Yamanaka, S. (2006) · Cell · doi:10.1016/j.cell.2006.07.024 · Cited by 26,673
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Self-citationPromoting Axon Regeneration in the Adult CNS by Modulation of the PTEN/mTOR Pathway
Park, K. K., Liu, K., Hu, Y., Smith, P. D., Wang, C., Cai, B., Xu, B., Connolly, L., Kramvis, I., Sahin, M., et al. (2008) · Science · doi:10.1126/science.1161566 · Cited by 1,686
Self-citationEigengene networks for studying the relationships between co-expression modules
Langfelder, P., & Horvath, S. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-54 · Cited by 867
Self-citationSustained axon regeneration induced by co-deletion of PTEN and SOCS3
Sun, F., Park, K. K., Belin, S., Wang, D., Lu, T., Chen, G., Zhang, K., Yeung, C., Feng, G., Yankner, B. A., et al. (2011) · Nature · doi:10.1038/nature10594 · Cited by 754
Self-citationAn atlas of combinatorial transcriptional regulation in mouse and man
Ravasi, T., Suzuki, H., Cannistraci, C. V., Katayama, S., Bajic, V. B., Tan, K., Akalin, A., Schmeier, S., Kanamori-Katayama, M., Bertin, N., et al. (2010) · Cell · doi:10.1016/j.cell.2010.01.044 · Cited by 715
Conservation and evolution of gene coexpression networks in human and chimpanzee brains
Oldham, M. C., Horvath, S., & Geschwind, D. H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605938103 · Cited by 566
Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430 · cited 2×
“This is consistent with the growing appreciation that genes do not act in isolation, but rather in coordinated networks in conjunction with other genes (Parikshak et al., 2015).”
Self-citationNeuroscience in the era of functional genomics and systems biology
Geschwind, D. H., & Konopka, G. (2009) · Nature · doi:10.1038/nature08537 · Cited by 213
Self-citation
Cited by
Spinal cord repair: advances in biology and technology
Courtine, G., & Sofroniew, M. V. (2019) · Nature Medicine · doi:10.1038/s41591-019-0475-6 · Cited by 508
SALMON: survival analysis learning with multi-omics neural networks on breast cancer
Huang, Z., Zhan, X., Xiang, S., Johnson, T. S., Helm, B., Yu, C. Y., Zhang, J., Salama, P., Rizkalla, M., Han, Z., et al. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00166 · Cited by 262
“Co-expression network analyses are used increasingly to reveal latent gene-gene interactions, biomarkers and novel gene functions (Horvath et al., 2012; Chandran et al., 2016; Han et al., 2016, 2017; Zhang and Huang, 2017; Xiang et al., 2018).”
BackgroundLatremoliere, A., Cheng, L., DeLisle, M., Wu, C., Chew, S., Hutchinson, E. B., Sheridan, A., Alexandre, C., Latremoliere, F., Sheu, S.-H., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.029 · Cited by 183
Self-citationAn active vesicle priming machinery suppresses axon regeneration upon adult CNS injury
Hilton, B. J., Husch, A., Schaffran, B., Lin, T.-C., Burnside, E. R., Dupraz, S., Schelski, M., Kim, J., Müller, J. A., Schoch, S., et al. (2022) · Neuron · doi:10.1016/j.neuron.2021.10.007 · Cited by 116
Rexach, J. E., Polioudakis, D., Yin, A., Swarup, V., Chang, T. S., Nguyen, T., Sarkar, A., Chen, L., Huang, J., Lin, L.-C., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108398 · Cited by 94
Self-citationIdentification of Conserved Proteomic Networks in Neurodegenerative Dementia
Swarup, V., Chang, T. S., Duong, D. M., Dammer, E. B., Dai, J., Lah, J. J., Johnson, E. C. B., Seyfried, N. T., Levey, A. I., & Geschwind, D. H. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107807 · Cited by 78
Self-citationIdentification of conserved proteomic networks in neurodegenerative dementia
Swarup, V., Chang, T. S., Duong, D. M., Dammer, E. B., Lah, J. J., Johnson, E. E. C. B., Seyfried, N. T., Levey, A. I., & Geschwind, D. H. (2019) · doi:10.1101/825802 · Cited by 78
Self-citationIntegrative genomics approach identifies conserved transcriptomic networks in Alzheimer’s disease
Morabito, S., Miyoshi, E., Michael, N., & Swarup, V. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa182 · Cited by 74
Small molecule modulators of chromatin remodeling: from neurodevelopment to neurodegeneration
Jiang, D., Li, T., Guo, C., Tang, T.-S., & Liu, H. (2023) · Cell & Bioscience · doi:10.1186/s13578-023-00953-4 · Cited by 54
Sekine, Y., Lin-Moore, A., Chenette, D. M., Wang, X., Jiang, Z., Cafferty, W. B., Hammarlund, M., & Strittmatter, S. M. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.058 · Cited by 52
Axonal Organelles as Molecular Platforms for Axon Growth and Regeneration after Injury
Petrova, V., Nieuwenhuis, B., Fawcett, J. W., & Eva, R. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22041798 · Cited by 32
Miyoshi, E., Morabito, S., & Swarup, V. (2021) · Neurobiology of Disease · doi:10.1016/j.nbd.2021.105530 · Cited by 7
Song, H., Peng, L., Chen, D., Fan, X., Hua, T., Ding, R., Deng, M., Chen, Q., Yang, M., & Yuan, H. (2025) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.70531 · Cited by 2
Metadata
- Authors
- Chandran, V., Coppola, G., Nawabi, H., Omura, T., Versano, R., Huebner, E. A., Zhang, A., Costigan, M., Yekkirala, A., Barrett, L., Blesch, A., Michaelevski, I., Davis-Turak, J., Gao, F., Langfelder, P., Horvath, S., He, Z., Benowitz, L., Fainzilber, M., Tuszynski, M., Woolf, C. J., & Geschwind, D. H.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 89
- Issue
- 5
- Pages
- 956-970
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2276418388
- Cited by
- 366
- References
- 10
- FWCI
- 21.66
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.