TY - JOUR AU - Biswas, Ashis Kumer AU - Kim, Dongchul AU - Kang, Mingon AU - Ding, Chris AU - Gao, Jean X. PY - 2017 DA - 2017/12/28 TI - Stable solution to l2,1-based robust inductive matrix completion and its application in linking long noncoding RNAs to human diseases JO - BMC Medical Genomics SP - 77 VL - 10 IS - 5 AB - A large number of long intergenic non-coding RNAs (lincRNAs) are linked to a broad spectrum of human diseases. The disease association with many other lincRNAs still remain as puzzle. Validation of such links between the two entities through biological experiments are expensive. However, a plethora lincRNA-data are available now, thanks to the High Throughput Sequencing (HTS) platforms, Genome Wide Association Studies (GWAS), etc, which opens the opportunity for cutting-edge machine learning and data mining approaches to extract meaningful relationships among lincRNAs and diseases. However, there are only a few in silico lincRNA-disease association inference tools available to date, and none of them utilizes side information of both the entities simultaneously in a single framework. SN - 1755-8794 UR - https://doi.org/10.1186/s12920-017-0310-1 DO - 10.1186/s12920-017-0310-1 ID - Biswas2017 ER -