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Cited by 354

The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.

A Review of the Methods for Human iPSC Derivation

Open access
Malik, Nasir, Rao, Mahendra S.·2013·Methods in Molecular Biology

Abstract

The ability to reprogram somatic cells to induced pluripotent stem cells (iPSCs) offers an opportunity to generate pluripotent patient-specific cell lines that can help model human diseases. These iPSC lines could also be powerful tools for drug discovery and the development of cellular transplantation therapies. Many methods exist for generating iPSC lines but those best suited for use in studying human diseases and developing therapies must be of adequate efficiency to produce iPSCs from samples that may be of limited abundance, capable of reprogramming cells from both skin fibroblasts and blood, and footprint-free. Several reprogramming techniques meet these criteria and can be utilized to derive iPSCs in projects with both basic scientific and therapeutic goals. Combining these reprogramming methods with small molecule modulators of signaling pathways can lead to successful generation of iPSCs from even the most recalcitrant patient-derived somatic cells.

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Metadata

Authors
Malik, N., & Rao, M. S.
Venue
Methods in Molecular Biology
Publisher
Humana Press
Published
2013
Volume
997
Pages
23-33
ISSN
  • 1064-3745 (ISSN-L)
  • 1940-6029
OpenAlex
W139824189
Cited by
354
References
44
FWCI
27.49
Type
book chapter
Language
en
Open access
green

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CoChat. (2026). Citation check: A Review of the Methods for Human iPSC Derivation. https://app.cochat.ai/papers/10.1007/978-1-62703-348-0_3
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Malik, N., & Rao, M. S. (2013). A Review of the Methods for Human iPSC Derivation. Methods in Molecular Biology. https://doi.org/10.1007/978-1-62703-348-0_3

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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.