Track topics on Twitter Track topics that are important to you
Matrix decomposition is a popular and fundamental approach in machine learning and data mining. It has been successfully applied into various fields. Most matrix decomposition methods focus on decomposing a data matrix from one single source. However, it is common that data are from different sources with heterogeneous noise. A few of matrix decomposition methods have been extended for such multi-view data integration and pattern discovery. While only few methods were designed to consider the heterogeneity of noise in such multi-view data for data integration explicitly. To this end, we propose a joint matrix decomposition framework (BJMD), which models the heterogeneity of noise by Gaussian distribution in a Bayesian framework. We develop two algorithms to solve this model: one is a variational Bayesian inference algorithm, which makes full use of the posterior distribution; and another is a maximum a posterior algorithm, which is more scalable and can be easily paralleled. Extensive experiments on synthetic and real-world datasets demonstrate that BJMD is superior or competitive to the state-of-the-art methods.
This article was published in the following journal.
Name: IEEE transactions on pattern analysis and machine intelligence
There is often limited amount of omics data to design predictive models in biomedicine. Knowing that these omics data come from underlying processes that may share common pathways and disease mechanis...
Recent advances in sequencing, mass spectrometry and cytometry technologies have enabled researchers to collect large-scale omics data from the same set of biological samples. The joint analysis of mu...
Biological databases are growing at an exponential rate, currently being among the major producers of Big Data, almost on par with commercial generators, such as YouTube or Twitter. While traditionall...
In patient care and medical research patient data often has to be transferred between different electronic systems. These systems can be very heterogeneous, sometimes even legacy systems, and thus, of...
Trapezoidal integration by linear interpolation of data points is by far the most commonly used method of cumulative flux calculations of nitrous oxide (NO) in studies that use flux chambers; however,...
Post-market prospective clinical study with a medical device. Data from patients that routinely receive a primary BPK-S-integration knee implant made of ceramic will be documented with a f...
Rheumatoid Arthritis (RA) is a chronic inflammatory disease characterized by joint swelling, joint tenderness and destruction of synovial joints, leading to severe disability and premature...
Sometime osseous reconstruction needs allogeneic bone, in this study we use Ostéopure™ from Ostéobanque d'Auvergne, which is a osseous matrix. However Ostéopure™ integration lasts a ...
The purpose of the study is to use a collagen matrix embedded with amniotic stem cells to speed up the maturation and integration of the collagen matrix in the wound bed and shorten total ...
This is a phase Ib multi-center, open-label study: escalation part followed by expansion part. The primary purpose of the Phase Ib CBCL201X2102C study is to characterize the safety and tol...
Insertion of viral DNA into host-cell DNA. This includes integration of phage DNA into bacterial DNA; (LYSOGENY); to form a PROPHAGE or integration of retroviral DNA into cellular DNA to form a PROVIRUS.
A heterogeneous-nuclear ribonucleoprotein found associated with the NUCLEAR MATRIX.
Cells on the luminal surface of the SYNOVIAL MEMBRANE. Type A synoviocytes are MACROPHAGES responsible for waste removal from the joint cavity. Fibroblast-like type B synoviocytes are involved in production of joint matrix constituents (e.g., HYALURONAN; COLLAGEN; and FIBRONECTIN).
Part of the body in humans and primates where the arms connect to the trunk. The shoulder has five joints; ACROMIOCLAVICULAR joint, CORACOCLAVICULAR joint, GLENOHUMERAL joint, scapulathoracic joint, and STERNOCLAVICULAR joint.
Information application based on a variety of coding methods to minimize the amount of data to be stored, retrieved, or transmitted. Data compression can be applied to various forms of data, such as images and signals. It is used to reduce costs and increase efficiency in the maintenance of large volumes of data.
Arthritis Fibromyalgia Gout Lupus Rheumatic Rheumatology is the medical specialty concerned with the diagnosis and management of disease involving joints, tendons, muscles, ligaments and associated structures (Oxford Medical Diction...
Standard antiretroviral therapy (ART) consists of the combination of at least three antiretroviral (ARV) drugs to maximally suppress the HIV virus and stop the progression of HIV disease. Huge reductions have been seen in rates of death and suffering whe...