Publications by authors named "Qing-Kang Wang"
Article Synopsis
- Gastric cancer (GC) is a major global health issue, prompting research into new treatment options focused on specific proteins MATN3 and ASPN that are linked to disease advancement.
- Analysis of data shows these proteins are overexpressed in GC tissues and associated with worse survival rates, indicating their potential role as biomarkers for the disease.
- Experimental studies reveal that MATN3 encourages cancer cell growth and spread, while inhibiting it leads to cell death; the combined effect of MATN3 and ASPN significantly boosts tumor behavior, suggesting this protein interaction could be a target for future GC therapies.
Background: Gastric cancer (GC) is a common malignancy with high morbidity. Long non-coding RNAs (LncRNAs) have been demonstrated to be critical post-transcriptional regulators in tumorigenesis. This study aimed to investigate the effect of LncRNA NEAT1 on the proliferation and metastasis of GC.
View Article and Find Full Text PDFEMMA: an efficient massive mapping algorithm using improved approximate mapping filtering.
Acta Biochim Biophys Sin (Shanghai)
December 2006
Efficient massive mapping algorithm (EMMA), an algorithm on efficiently mapping massive cDNAs onto genomic sequences, has recently been developed. The process of mapping massive cDNAs onto genomic sequences has been improved using more approximate mapping filtering based on an enhanced suffix array coupled with a pruned fast hash table, algorithms of block alignment extensions, and k-longest paths. When compared with the classical BLAT software in this field, the computing of EMMA ranges from two to forty-one times faster under similar prediction precisions.
View Article and Find Full Text PDF