TY - GEN
T1 - A guided network propagation approach to identify disease genes that combines prior and new information
AU - Hristov, Borislav H.
AU - Chazelle, Bernard
AU - Singh, Mona
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Summary. A major challenge in biomedical data science is to identify the causal genes underlying complex genetic diseases. Despite the massive influx of genome sequencing data, identifying disease-relevant genes remains difficult as individuals with the same disease may share very few, if any, genetic variants.
AB - Summary. A major challenge in biomedical data science is to identify the causal genes underlying complex genetic diseases. Despite the massive influx of genome sequencing data, identifying disease-relevant genes remains difficult as individuals with the same disease may share very few, if any, genetic variants.
UR - http://www.scopus.com/inward/record.url?scp=85084250544&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084250544&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-45257-5_25
DO - 10.1007/978-3-030-45257-5_25
M3 - Conference contribution
AN - SCOPUS:85084250544
SN - 9783030452568
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 251
EP - 252
BT - Research in Computational Molecular Biology - 24th Annual International Conference, RECOMB 2020, Proceedings
A2 - Schwartz, Russell
PB - Springer
T2 - 24th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020
Y2 - 10 May 2020 through 13 May 2020
ER -