Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach.
- DOI
- 10.1016/j.fsigen.2019.102150
- Published
- 2019-08-23
- Container
- Forensic Sci Int Genet
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.fsigen.2019.102150,
title = {Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach.},
author = {Benschop CCG and van der Linden J and Hoogenboom J and Ypma R and Haned H.},
year = {2019},
journal = {Forensic Sci Int Genet},
doi = {10.1016/j.fsigen.2019.102150},
url = {https://doi.org/10.1016/j.fsigen.2019.102150}
}RIS
TY - JOUR TI - Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach. AU - Benschop CCG AU - van der Linden J AU - Hoogenboom J AU - Ypma R AU - Haned H. PY - 2019 JO - Forensic Sci Int Genet DO - 10.1016/j.fsigen.2019.102150 UR - https://doi.org/10.1016/j.fsigen.2019.102150 ER -
APA
CCG, B., J, V. D. L., J, H., R, Y., & H., H. (2019). Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach.. Forensic Sci Int Genet. https://doi.org/10.1016/j.fsigen.2019.102150
Source records
- europe-pmc · retrieved 2026-09-27T02:15:48.643Z