In vitro stress assays are commonly used to study the responses of plants to abiotic stress
and to assess stress tolerance. A literature review reveals that most studies use very high …

Text mining for the life sciences aims to aid database curation, knowledge summarization
and information retrieval through the automated processing of biomedical texts. To provide …

With the advent of next generation genome sequencing, the number of sequenced algal
genomes and transcriptomes is rapidly growing. Although a few genome portals exist to browse …

Motivation: In the field of biomolecular text mining, black box behavior of machine learning
systems currently limits understanding of the true nature of the predictions. However, feature …

Background Differential networks have recently been introduced as a powerful way to study
the dynamic rewiring capabilities of an interactome in response to changing environmental …

Because of the intrinsic complexity of natural language, automatically extracting accurate
information from text remains a challenge. We have applied rich featurevectors derived from …

During the past few years, several novel text mining algorithms have been developed in the
context of the BioNLP Shared Tasks on Event Extraction. These algorithms typically aim at …

Technological advancements in the field of genetics have led not only to an abundance of
experimental data, but also caused an exponential increase of the number of published …

In comparative genomics, functional annotations are transferred from one organism to another
relying on sequence similarity. With more than 20 million citations in PubMed, text mining …

Despite the availability of various data repositories for plant research, a wealth of information
currently remains hidden within the biomolecular literature. Text mining provides the …