Zobrazeno 1 - 10
of 5 851
pro vyhledávání: '"Quantitative Biology - Genomics"'
The increase in high-dimensional multiomics data demands advanced integration models to capture the complexity of human diseases. Graph-based deep learning integration models, despite their promise, struggle with small patient cohorts and high-dimens
Externí odkaz:
http://arxiv.org/abs/2408.02845
Autor:
Abdelwahab, Omar, Torkamaneh, Davoud
Variant calling refinement is crucial for distinguishing true genetic variants from technical artifacts in high-throughput sequencing data. Manual review is time-consuming while heuristic filtering often lacks optimal solutions. Traditional variant c
Externí odkaz:
http://arxiv.org/abs/2408.00659
Autor:
Guo, Boyi, Ling, Wodan, Kwon, Sang Ho, Panwar, Pratibha, Ghazanfar, Shila, Martinowich, Keri, Hicks, Stephanie C.
Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. As the cost of generating these data decreases, these technologies provide an exciti
Externí odkaz:
http://arxiv.org/abs/2408.00367
Autor:
Hartung, Michael, Maier, Andreas, Delgado-Chaves, Fernando, Burankova, Yuliya, Isaeva, Olga I., Patroni, Fábio Malta de Sá, He, Daniel, Shannon, Casey, Kaufmann, Katharina, Lohmann, Jens, Savchik, Alexey, Hartebrodt, Anne, Chervontseva, Zoe, Firoozbakht, Farzaneh, Probul, Niklas, Zotova, Evgenia, Tsoy, Olga, Blumenthal, David B., Ester, Martin, Laske, Tanja, Baumbach, Jan, Zolotareva, Olga
Most complex diseases, including cancer and non-malignant diseases like asthma, have distinct molecular subtypes that require distinct clinical approaches. However, existing computational patient stratification methods have been benchmarked almost ex
Externí odkaz:
http://arxiv.org/abs/2408.00200
Polygenic risk scores (PRSs) can significantly enhance breast cancer risk prediction when combined with clinical risk factor data. While many studies have explored the value-add of PRSs, little is known about the potential impact of gene-by-gene or g
Externí odkaz:
http://arxiv.org/abs/2407.20978
Gaussian graphical models can be used to extract conditional dependencies between the features of the dataset. This is often done by making an independence assumption about the samples, but this assumption is rarely satisfied in reality. However, sta
Externí odkaz:
http://arxiv.org/abs/2407.19892
Autor:
Andersen, Mikkel Meyer, Kampmann, Marie-Louise, Jepsen, Alberte Honoré, Morling, Niels, Eriksen, Poul Svante, Børsting, Claus, Andersen, Jeppe Dyrberg
In forensic genetics, short tandem repeats (STRs) are used for human identification (HID). Degraded biological trace samples with low amounts of short DNA fragments (low-quality DNA samples) pose a challenge for STR typing. Predefined single nucleoti
Externí odkaz:
http://arxiv.org/abs/2407.19761
Autor:
Castro-Prado, Fernando
[PhD thesis of FCP.] Nowadays, genetics studies large amounts of very diverse variables. Mathematical statistics has evolved in parallel to its applications, with much recent interest high-dimensional settings. In the genetics of human common disease
Externí odkaz:
http://arxiv.org/abs/2407.19624
Autor:
Dimonaco, Nicholas J.
PyamilySeq is a Python-based tool designed for interpretable gene clustering and pangenomic inference, supporting analyses at both species and genus levels. It facilitates the clustering of gene sequences into families based on sequence similarity us
Externí odkaz:
http://arxiv.org/abs/2407.19328
Interpreting artificial neural networks to detect genome-wide association signals for complex traits
Investigating the genetic architecture of complex diseases is challenging due to the highly polygenic and interactive landscape of genetic and environmental factors. Although genome-wide association studies (GWAS) have identified thousands of variant
Externí odkaz:
http://arxiv.org/abs/2407.18811