Welcome to the Data Center of Species Inspired Research for Innovative Treatments (SPIRIT) Most tissue damage from infectious disease is caused by secondary inflammation elicited in the host. Furthermore, identical pro-inflammatory stimuli from the same pathogen load causes markedly different amounts of inflammation in different species, different hosts, and even within a single individual. Given […]
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
Knowledge-Based Network Analysis of Genomic Data Read More »
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
Description The ability to reliably, robustly, and reproducibly detect quantitative protein abundance from biofluids and tissues of patients would have many applications in both research and clinical medicine. SGTC enjoys a long-standing collaboration with the laboratory of Richard Smith (Pacific Northwest National Laboratory), one of the leading groups developing the liquid-chromatography mass spectrometry (LC-MS) approach
High-throughput Proteomics for Biomarker Discovery Read More »
We collaborated with biotech companies such as Ion Torrent and developed some of the original base calling algorithms for NGS platforms. For inquires, please contact wzxiao at stanford.edu
Developing Base Calling Algorithms for NGS platforms Read More »
Introduction Glue Grant Human Transcriptome Array (GG-H) is a collaboration result between Stanford Genome Technology Center, Wing Wong’s lab at Stanford, Affymetrix Inc and the Inflammation and Host Response to Injury program (“Glue Grant”). The array has been comprehsively designed to interrogate various apects of the transcriptome, incuding gene expression, alternative splicing, detection of coding SNPs and non-coding transcription. With
Development of Next-Gen Human Transcriptome Array Read More »
Chromosome abnormalities, including losses and gains of entire chromosomes, alterations of chromosome arms, focal amplifications and deletions, and rearrangements, are common characteristics of cancer genome. Detection of such alterations in an early stage provides an opportunity of cancer prevention. We are studying tumor-derived chromosomal alterations, as well as single base mutations through the analysis of
Detection of Rare Genomic Changes in Patients Read More »
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
Multiple Variant Survival Analysis Read More »
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
Modeling of Immune Repertoire Read More »
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
Junction-specific peptide detection and alternative splicing Read More »