REFERENCES

1. Pereira R, Phillips C, Alves C, Amorim A, Carracedo A, Gusmão L. A new multiplex for human identification using insertion/deletion polymorphisms. Electrophoresis. 2009;30:3682-90.

2. Manta F, Caiafa A, Pereira R, et al. Indel markers: genetic diversity of 38 polymorphisms in Brazilian populations and application in a paternity investigation with post mortem material. Forensic Sci Int Genet. 2012;6:658-61.

3. Zhang YD, Shen CM, Jin R, et al. Forensic evaluation and population genetic study of 30 insertion/deletion polymorphisms in a Chinese Yi group. Electrophoresis. 2015;36:1196-201.

4. Fan H, He Y, Li S, et al. Systematic evaluation of a novel 6-dye direct and multiplex PCR-CE-based InDel typing system for forensic purposes. Front Genet. 2021;12:744645.

5. Liu J, Du W, Jiang L, et al. Development and validation of a forensic multiplex InDel assay: the AGCU InDel 60 kit. Electrophoresis. 2022;43:1871-81.

6. Chen X, Nie S, Hu L, et al. Forensic efficacy evaluation and genetic structure exploration of the Yunnan Miao group by a multiplex InDel panel. Electrophoresis. 2022;43:1765-73.

7. Fang Y, Zhao C, Jin X, et al. Genetic characterization evaluation of a novel multiple system containing 57 deletion/insertion polymorphic loci with short amplicons in Hunan Han population and its intercontinental populations analyses. Gene. 2022;809:146006.

8. Chen M, Cui W, Bai X, et al. Comprehensive evaluations of individual discrimination, kinship analysis, genetic relationship exploration and biogeographic origin prediction in Chinese Dongxiang group by a 60-plex DIP panel. Hereditas. 2023;160:14.

9. Xu H, Nie S, Hu L, et al. Comprehensive understanding the forensic systematic effectiveness in Chinese Yunnan Hani group and intercontinental population Architecture differentiation analyses via a novel set of autosomal InDel markers. Front Biosci. 2023;28:5.

10. Chakraborty R, Jin L. Determination of relatedness between individuals using DNA fingerprinting. Hum Biol. 1993;65:875-95.

11. Weir BS, Anderson AD, Hepler AB. Genetic relatedness analysis: modern data and new challenges. Nat Rev Genet. 2006;7:771-80.

12. Kling D, Tillmar A. Forensic genealogy-A comparison of methods to infer distant relationships based on dense SNP data. Forensic Sci Int Genet. 2019;42:113-24.

13. Coble MD, Buckleton J, Butler JM, et al. DNA Commission of the International Society for Forensic Genetics: recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications. Forensic Sci Int Genet. 2016;25:191-7.

14. Heinrich V, Kamphans T, Mundlos S, Robinson PN, Krawitz PM. A likelihood ratio-based method to predict exact pedigrees for complex families from next-generation sequencing data. Bioinformatics. 2017;33:72-8.

15. Galván-Femenía I, Barceló-Vidal C, Sumoy L, Moreno V, de Cid R, Graffelman J. A likelihood ratio approach for identifying three-quarter siblings in genetic databases. Heredity. 2021;126:537-47.

16. Xu Q, Wang Z, Kong Q, et al. Improving the system power of complex kinship analysis by combining multiple systems. Forensic Sci Int Genet. 2022;60:102741.

17. Chen T, Guestrin C. XGBoost: A scalable tree boosting system. In: KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Association for Computing Machinery, New York, NY, USA, 2016: pp. 785-94.

18. Ke G, Meng Q, Finley T, et al. LightGBM: a highly efficient gradient boosting decision tree. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. Red Hook, NY, USA: Curran Associates Inc.; 2017. p. 3149-57. Available from https://hal.science/hal-03953007/ [accessed 30 March 2026].

19. Byrska-Bishop M, Evani US, Zhao X, et al. ; Human Genome Structural Variation Consortium. High-coverage whole-genome sequencing of the expanded 1000 genomes project cohort including 602 trios. Cell. 2022;185:3426-3440.e19.

20. Wang M, Du W, Tang R, et al. Genomic history and forensic characteristics of Sherpa highlanders on the Tibetan Plateau inferred from high-resolution InDel panel and genome-wide SNPs. Forensic Sci Int Genet. 2022;56:102633.

21. Gouy A, Zieger M. STRAF-A convenient online tool for STR data evaluation in forensic genetics. Forensic Sci Int Genet. 2017;30:148-51.

22. Excoffier L, Lischer HE. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010;10:564-7.

23. Kling D, Tillmar AO, Egeland T. Familias 3 - extensions and new functionality. Forensic Sci Int Genet. 2014;13:121-7.

24. Geman S, Bienenstock E, Doursat R. Neural networks and the bias/variance dilemma. Neural Comput. 1992;4:1-58.

25. Neal B. On the bias-variance tradeoff: textbooks need an update. arXiv. 2019;arXiv:1912.08286.

26. LaRue BL, Ge J, King JL, Budowle B. A validation study of the Qiagen Investigator DIPplex® kit; an INDEL-based assay for human identification. Int J Legal Med. 2012;126:533-40.

27. Pereira R, Gusmão L. Capillary electrophoresis of 38 noncoding biallelic mini-Indels for degraded samples and as complementary tool in paternity testing. Methods Mol Biol. 2012;830:141-57.

28. Alladio E, Poggiali B, Cosenza G, Pilli E. Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field. Sci Rep. 2022;12:8974.

29. Sun K, Yao Y, Yun L, et al. Application of machine learning for ancestry inference using multi-InDel markers. Forensic Sci Int Genet. 2022;59:102702.

30. Pilli E, Morelli S, Poggiali B, Alladio E. Biogeographical ancestry, variable selection, and PLS-DA method: a new panel to assess ancestry in forensic samples via MPS technology. Forensic Sci Int Genet. 2023;62:102806.

31. Wolpert D, Macready W. No free lunch theorems for optimization. IEEE Trans Evol Comput. 1997;1:67-82.

32. Prokhorenkova L, Gusev G, Vorobev A, Dorogush AV, Gulin A. CatBoost: unbiased boosting with categorical features. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems; Red Hook, NY, USA: Curran Associates Inc.; 2018. p. 6639-49. Available from https://proceedings.neurips.cc/paper_files/paper/2018/file/14491b756b3a51daac41c24863285549-Paper.pdf. [accessed 30 March 2026].

Journal of Translational Genetics and Genomics
ISSN 2578-5281 (Online)
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