Add to ORKGClustering microarray-derived gene lists through implicit literature relationship
A new unsupervised gene clustering algorithm based on the integration of biological knowledge into e...
Literature mining is the process of extracting and combining facts from scientific publications. In ...
Keeping up with the rapidly growing literature has become virtually impossible for most scientists. ...
Learning string similarity measures for gene/protein name dictionary look-up using logistic regressi...
Motivation:Network reconstruction of biological entities is very impor-tant for understanding biolog...
Speeding up tandem mass spectrometry database search: metric embeddings and fast near neighbor searc
textabstractThis thesis describes the development of text-mining algorithms for molecular biology,...
Boosting multiclass learning with repeating codes and weak detectors for protein subcellular localiz...
Partitioning closely related genes into clusters has become an important element of practically all ...
An efficient method for the detection and elimination of systematic error in high-throughput screeni...
A major challenge for functional and comparative genomics resource development is the extraction of ...
Biomedical text-mining have great promise to improve the usefulness of genomic researchers. The goal...
The past decade has seen a tremendous growth in the amount of experimental and computational biomedi...
Summary: Often, the most informative genes have to be selected from different gene sets and several ...
Biomedical scientific literature is becoming a valuable information sourcethat includes a hu...
A new unsupervised gene clustering algorithm based on the integration of biological knowledge into e...
Literature mining is the process of extracting and combining facts from scientific publications. In ...
Keeping up with the rapidly growing literature has become virtually impossible for most scientists. ...
Learning string similarity measures for gene/protein name dictionary look-up using logistic regressi...
Motivation:Network reconstruction of biological entities is very impor-tant for understanding biolog...
Speeding up tandem mass spectrometry database search: metric embeddings and fast near neighbor searc
textabstractThis thesis describes the development of text-mining algorithms for molecular biology,...
Boosting multiclass learning with repeating codes and weak detectors for protein subcellular localiz...
Partitioning closely related genes into clusters has become an important element of practically all ...
An efficient method for the detection and elimination of systematic error in high-throughput screeni...
A major challenge for functional and comparative genomics resource development is the extraction of ...
Biomedical text-mining have great promise to improve the usefulness of genomic researchers. The goal...
The past decade has seen a tremendous growth in the amount of experimental and computational biomedi...
Summary: Often, the most informative genes have to be selected from different gene sets and several ...
Biomedical scientific literature is becoming a valuable information sourcethat includes a hu...
A new unsupervised gene clustering algorithm based on the integration of biological knowledge into e...
Literature mining is the process of extracting and combining facts from scientific publications. In ...
Keeping up with the rapidly growing literature has become virtually impossible for most scientists. ...