Bayesian methods are valuable, inter alia, whenever there is a need to extract information from data that is uncertain or subject to any kind of error or noise (including measurem...
Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely ap...
Bioinformatics data is growing at a phenomenal rate. Besides the exponential growth of individual databases, the number of data depositories is increasing too. Because of the comp...
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
Discovering human disease-causing genes (disease genes in short) is one of the most challenging problems in bioinformatics and biomedicine, as most diseases are related in some wa...