Development of Computational Methods

Knowledge-Based Network Analysis of Genomic Data

INTRODUCTION Extracting new biological insight from high throughput genomic studies of human diseases is a daunting challenge, limited by difficulties in recognizing and evaluating relevant biological processes from the immense quantities of experimental data. Cluster and principal component analyses describe overall changes in apparent gene expression, but provide few insights into the biological processes and […]

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Knowledge-based Reconstruction of mRNA Transcripts with Short Sequencing Reads for Transcriptome Research

INTRODUCTION The knowledge-based transcript reconstruction algorithm was developed to aid the design and analysis of next-generation transcriptome arrays, using RNA-Seq data in NCBI SRA (1) and annotation databases of RNA transcripts, such as RefSeq, Ensembl and UCSC known genes. The algorithm combines information in the RNA-Seq data and in the reference annotations to define a

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Multiple Variant Survival Analysis

Project Summary A complex disease often affects the functions of multiple organs of the human body. In intensive care, the recovery of major organ functions is essential to patient’s overall recovery averting death. As part of the Glue Grant Consortium, the Inflammation and the Host Response to Injury, we have collected functional trajectories of six

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Modeling of Immune Repertoire

Project Summary  The evolution of a cancer system consisting of cancer clones and normal cells is a complex and dynamic process with multiple interacting factors including clonal expansion, somatic mutation, and sequential selection. As a typical example, in patients with chronic lymphocytic leukemia (CLL), a monoclonal population of transformed B cells expands to dominate the

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Junction-specific peptide detection and alternative splicing

We are developing a computational method to analyze proteomics data for the detection of junction-specific peptide and alternative splicing. In details, we will Identify the human junction-specific peptides using information from the exon database we created; Assign confidence for junction-specific peptides using the fragment ions in MS/MS spectra; Modeling alternative splicing using junction-specific peptide information

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Analysis of Alternative Splicing

Description JETTA is an integrated software tool for gene and exon expression calculation and alternative splicing analyses. It can be applied to the analysis and visualization of both exon-junction array and RNA-Seq data.See more about JETTA Updates 05/18/11: version 1.0.0— Interfaces for RNA-Seq data was added.10/07/10: version 0.6.0— GUI was built, plotting asa output was

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Time course multifactor analysis

Description Time-course microarray experiment is capable of capturing the dynamic profile of genomic response to treatment factors. The profile contains valuable information for researchers to identify possible genetic factors that lead to different clinical outcomes, which can help directing future investigation. We developed a general statistical method to extract gene-specific temporal patterns to the interaction

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Prediction of Patient Outcomes from Longitudinal Microarray Data

Purpose Time course gene expression profiling is increasingly applied in biomedical research to monitor the progression of diseases and effects of drug treatments. An important goal of the computational analysis is to predict clinical outcomes based on microarray data of patients over time. . However, most existing approaches of prediction use data at one time

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