A5113567130- Data Management and Algorithms
- Data Mining Algorithms and Applications
- Topic Modeling
- Advanced Database Systems and Queries
- Transplantation: Methods and Outcomes
- Natural Language Processing Techniques
- Gene expression and cancer classification
- Renal Transplantation Outcomes and Treatments
- Genomic variations and chromosomal abnormalities
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Advanced Text Analysis Techniques
- Logic, Reasoning, and Knowledge
- Semantic Web and Ontologies
- Chromatin Remodeling and Cancer
- Algorithms and Data Compression
- Rough Sets and Fuzzy Logic
- Anomaly Detection Techniques and Applications
- Molecular Biology Techniques and Applications
- Organ Transplantation Techniques and Outcomes
- Privacy-Preserving Technologies in Data
- Viral Infections and Immunology Research
- Data Quality and Management
- RNA modifications and cancer
- Advanced Statistical Methods and Models
- Bioinformatics and Genomic Networks
Institute for Systems Biology
2021-2025
University of British Columbia
2016-2025
University of Washington
2021-2025
Prevention of Organ Failure
2015-2024
St. Paul's Hospital
2017-2024
University of Pennsylvania
2022-2024
Baebies (United States)
2024
Singapore Science Park
2024
University of British Columbia Hospital
2001-2023
InSysBio (Russia)
2021-2023
For many KDD applications, such as detecting criminal activities in E-commerce, finding the rare instances or outliers, can be more interesting than common patterns. Existing work outlier detection regards being an a binary property. In this paper, we contend that for scenarios, it is meaningful to assign each object degree of outlier. This called local factor (LOF) object. It depends on how isolated with respect surrounding neighborhood. We give detailed formal analysis showing LOF enjoys...
For many KDD applications, such as detecting criminal activities in E-commerce, finding the rare instances or outliers, can be more interesting than common patterns. Existing work outlier detection regards being an a binary property. In this paper, we contend that for scenarios, it is meaningful to assign each object degree of outlier. This called local factor (LOF) object. It depends on how isolated with respect surrounding neighborhood. We give detailed formal analysis showing LOF enjoys...
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, paper has three main contributions. First, it proposes a new clustering method called CLARANS, whose aim to identify structures be present data. Experimental results indicate that, when compared with existing methods, CLARANS very efficient effective. Second, investigates how can handle not only point objects, but also polygon objects efficiently....
Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation 309 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data patient-reported symptoms. resolved four PASC-anticipating at the time diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, specific...
From the standpoint of supporting human-centered discovery knowledge, present-day model mining association rules suffers from following serious shortcomings: (i) lack user exploration and control, (ii) focus, (iii) rigid notion relationships. In effect, this functions as a black-box, admitting little interaction in between. We propose, paper, an architecture that opens up supports constraint-based, exploratory associations. The foundation is rich set constraint constructs, including domain,...
Software developers are often faced with modification tasks that involve source which is spread across a code base. Some dependencies between code, such as those written in different languages, difficult to determine using existing static and dynamic analyses. To augment analyses help identify relevant during task, we have developed an approach applies data mining techniques change patterns - sets of files were changed together frequently the past from history Our hypothesis can be used...
Continuous BRAF inhibition of mutant melanomas triggers a series cell state changes that lead to therapy resistance and escape from immune control before establishing acquired genetically. We used genome-wide transcriptomics single-cell phenotyping explore the response kinetics for panel patient-derived BRAFV600 -mutant melanoma lines. A subset plastic lines, which followed trajectory covering multiple known transitions, provided models more detailed biophysical investigations. Markov...
We propose a novel abstractive summarization system for product reviews by taking advantage of their discourse structure.First, we apply parser to each review and obtain tree representation every review.We then modify the trees such that leaf node only contains aspect words.Second, aggregate generate graph.We select subgraph representing most important aspects rhetorical relations between them using PageRank algorithm, transform selected into an tree.Finally, natural language summary...
Clauses and sentences rarely stand on their own in an actual discourse; rather, the relationship between them carries important information that allows discourse to express a meaning as whole beyond sum of its individual parts. Rhetorical analysis seeks uncover this coherence structure. In article, we present CODRA— COmplete probabilistic Discriminative framework for performing Analysis accordance with Structure Theory, which posits tree representation discourse. CODRA comprises segmenter...
In this paper, we attempt to approximate and index a d- dimensional (d ≥ 1) spatio-temporal trajectory with low order continuous polynomial. There are many possible ways choose the polynomial, including (continuous)Fourier transforms, splines, non-linear regressino, etc. Some of these possiblities have indeed been studied beofre. We hypothesize that one best possibilities is polynomial minimizes maximum deviation from true value, which called minimax Minimax approximation particularly...
Capturing knowledge from free-form evaluative texts about an entity is a challenging task. New techniques of feature extraction, polarity determination and strength evaluation have been proposed. Feature extraction particularly important to the task as it provides underpinnings extracted knowledge. The work in this paper introduces improved method for that draws on existing unsupervised method. By including user-specific prior evaluated entity, we turn into one term similarity by mapping...
Abstract Purpose: Current chemotherapeutic regimens have only modest benefit for non–small cell lung cancer (NSCLC) patients. Cumulative toxicities/drug resistance limit chemotherapy given after the first-line regimen. For personalized chemotherapy, clinically relevant NSCLC models are needed quickly predicting most effective therapy with curative intent. In this study, first generation subrenal capsule xenografts of primary NSCLCs were examined (a) determining responses to conventional and...
Abstract Motivation: Array comparative genomic hybridization (aCGH) is a pervasive technique used to identify chromosomal aberrations in human diseases, including cancer. Aberrations are defined as regions of increased or decreased DNA copy number, relative normal sample. Accurately identifying the locations these has many important medical applications. Unfortunately, observed number changes often corrupted by various sources noise, making boundaries hard detect. One popular current uses...