Autism spectrum disorder (ASD) research has yet to leverage “big data” on the same scale
as other fields; however, advancements in easy, affordable data collection and analysis may …

Despite considerable progress in genome-and proteome-based high-throughput screening
methods and in rational drug design, the increase in approved drugs in the past decade did …

Background One challenge facing biologists is to tease out useful information from massive
data sets for further analysis. A pathway-based analysis may shed light by projecting …

For the average biologist, hands-on literature mining currently means a keyword search in
PubMed. However, methods for extracting biomedical facts from the scientific literature have …

Assembly of a transcriptional and post‐translational molecular interaction network in B cells,
the human B‐cell interactome (HBCI), reveals a hierarchical, transcriptional control module …

In this work, we conducted a visualized bibliometric analysis to map the research trends of
machine learning in engineering (MLE) based on articles indexed in the Web of Science …

The recent years have witnessed a rapid increase in the number of scientific articles in
biomedical domain. These literature are mostly available and readily accessible in …

Text mining is defined by Hearst (1999) as the automatic discovery of new, previously
unknown, information from unstructured textual data. This is often seen as comprising of …

With biomedical literature increasing at a rate of several thousand papers per week, it is
impossible to keep abreast of all developments; therefore, automated means to manage the …

Data generation is no longer the limiting factor in advancing biological research. In addition,
data integration, analysis, and interpretation have become key bottlenecks and challenges …