We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
To address the challenges of information integration and retrieval, the computational genomics community increasingly has come to rely on the methodology of creating annotations o...
David P. Hill, Barry Smith, Monica S. McAndrews-Hi...
Background: Single-pass, partial sequencing of complementary DNA (cDNA) libraries generates thousands of chromatograms that are processed into high quality expressed sequence tags...
Charu G. Kumar, Richard LeDuc, George Gong, Levan ...
Background: In 2004, we presented a web resource for stimulating the search for novel RNAs, RNA-As-Graphs (RAG), which classified, catalogued, and predicted RNA secondary structur...
Joseph A. Izzo, Namhee Kim, Shereef Elmetwaly, Tam...
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...