Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
As the rise in availability of natural language data, the underlying language structures can be better learned and play the important roles in many natural language processing tasks. Although the neural language representation models...
In recent years, researchers have become increasingly interested in deep learning. Extensive and high-quality data are essential for deep learning. For example, PubMed is a popular and free search engine with more than 30 million...
Biomedial literature usually contains cutting edge research results on biomedical entities, in particular the relation between them, for example the interaction between two proteins. However, the ever-increasing volume in the literature...
Utilizing high throughput gene expression data stored in public archives not only saves research time and cost but also enhances the power of its statistical support. However, gene expression profiling data can be obtained from many...
Gaussian processes are not uncommon in various fields of science such as engineering, genomics, quantitative finance and astronomy, to name a few. In fact, such processes are special cases in a broader class of data known as functional...
Reusability is part of the FAIR data principle, which aims to make data Findable, Accessible, Interoperable, and Reusable. One of the current efforts to increase the reusability of public genomics data has been to focus on the inclusion...
Proteins and RNAs are molecular machines performing biological functions in the cells of all organisms. Automatic comparison and classification of these biomolecules are fundamental yet open problems in the field of Structural...
Background: Genomic and epigenomic data analyses has been a popular research area in the 21st century. Common research problems include detecting differentially expressed genes between groups, clustering and classification using genomic...
With the rapid development of Artificial Intelligence, Machine Learning technologies have entered a fast-evolving era. This dissertation covers application studies of various algorithms ranging from traditional machine learning methods...
In the genetic study, the advance of high-through technology allowed scientists to collect data on a larger scale and with more complexity. Thus, it is common that the collected data is high-dimension and heterogenous, i.e. the number of...
Gene-expression data profile are widely used in all kinds of biomedical studies especially in cancer research. This dissertation work focus on solving the problem of how to combine datasets arising from different studies. Of particular...
Big data has brought both opportunities and challenges to our research community. Complex models can be built with large volumes of data researchers have never had access before. In this study we explore the structure learning of...
Large volumes of genomic data and new scientific discoveries in biomedical research are being made every day by laboratories in both academia and industry. However, two issues severely affect the usability of so-called biomedical big...
Work is presented from two projects, each involving an application of machine learning to precision medicine. The first project was for the Document Triage Task of the BioCreative VI Precision Medicine Track. Teams were asked to build...
We present two studies incorporating existing biological knowledge into differential gene expression analysis that attempt to place the results within a broader biological context. The studies investigate breast cancer health disparity...
Two main challenges in computational biology are identify differential expressed genes from gene expression data and find out biological variable interactions from genomics data. This dissertation presents two studies in each of them. In...
In the past decade, there has been an exponential increase in the volume of biomedical literature, creating a wealth of life sciences knowledge in need of automated curation. This automated extraction process is termed Information...
Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
