The Bioinformatics Shared Resource provides cutting-edge computational and systems biology support to the Institute and its NCI-designated Cancer Center. We specialize in omics data analysis, multi-omics data integration, network and pathway analysis, and machine learning. Different levels of data analyses are provided, based on the complexity of researchers’ data sets. This may include automated pipeline-based analyses, customized deep data mining, development and application of machine learning models, and hypothesis driven in-silico drug discovery. Our focus is to help researchers put data into biological contexts across various disease areas, and to create testable hypotheses and understandable biological processes.
We also provide Bioinformatics classes and training for the entire Cancer Center and Sanford Burnham Prebys community. Both internal and external customers are charged at assigned hourly rates.
The areas we focus on include:
- Data mining of Next Generation Sequencing (NGS) data sets, including:
- RNA-Seq, ChIP-Seq, ATAC-Seq, DNA Methylation etc.
- Data integration of transcriptomics, genomics, proteomics, and epigenomics data sets
- Network and pathway analyses using customized algorithms and commercially available software, including Regulattice, Ingenuity Pathway Analysis, Metacore, GSEA etc.
- Machine learning applications and implementation
- High Throughput Screening data analysis
- In silico drug discovery, biomarker identification, and toxicogenomics
- Training and consultation on bioinformatics
- Grant and letter-of-support writing services
We are looking for a talented candidate for a Bioinformatics Specialist position in this challenging computational team. The successful candidate should have strong genomics, computational and statistical skills, great communication and interpersonal skills, and be able to independently solve scientific projects.
We also welcome undergraduate or graduate interns for short term computational biology projects.
Please contact Dr. Jun Yin for more information.
Assistance is provided in the following areas:
- Systems Biology Support
Generating and Analyzing networks and pathways to produce testable hypotheses, to discover mechanisms of drug action and new drug targets.
- Next-Generation Sequencing Data Analysis
From Reads to Biology (RNA-Seq, ChiP-Seq, ATAC-Seq, DNA-Seq, exome sequencing, targeted resequencing, SNP and indel detection, single cell analysis and more)
- Proteomics, Microarray, RNA-seq, and related analysis
Experiment design, power analysis, estimation of the minimum number of animals required etc. For advanced statistical support we have a consulting agreement with PhD level statistician
- Integrative analysis of multi-omics data
- Grant Preparation Assistance
- Bioinformatics classes, tutorials and trainings
- Results reports sent to the customer include description of the analysis, data tables, figures and power point presentation with analysis details
Jun Yin, Ph.D.
(858) 795-5200 ext. 5085
Email Jun Yin
Equipment & Resources
We have advanced hardware and large collection of software to solve your research problems. The software collections include commercially licensed software suites, including Ingenuity Pathway Analysis (IPA), Omicsoft Array Suite, Oncomine, NextBio, MetaCore; and open source software and databases such as Cytoscape, Broad Institute Genome Analysis ToolKit (GATK), GSEA; and customized algorithm and pipeline development using R Bioconductor, Perl and Python. We actively use data from public databases (GEO, TCGA, UCSC Cancer Genome Browser, CCLE, and others) for biomarker discovery, survival analysis and predictive modeling.
We have constructed automated computational pipelines using best-practices for RNA-Seq, ChIP-Seq, ATAC-Seq etc. We are also efficient in analyzing CRISPR, miCLIP, DNA Methylation, Single Cell Sequencing data sets. We have strong industrial experience in drug discovery, high-throughput screening, biomarker discovery, and toxicogenomics.
Our Regulattice pipeline for advanced machine learning in identifying actionable cancer drivers has been updated to accommodate additional functional and biological validation. RNA-Seq and clinical data from twenty-three major cancer cohorts from TCGA have been analyzed using our Viper/Regulattice protocol and made publicly available (regulattice.sbpdiscovery.org username: demo password: demo1).
To discuss your project needs, please call (858) 795-5200 ext. 5058 or email jyin@SBPdiscovery.org.
|Bioinformatics Services||Internal Subsidized||Internal||External Non-Profit||External For-Profit|
|Bioinformatics Custom Data Analysis/Application||hour||$50||$62.50||$67.50||$131.50|
|Statistics data Analysis||hour||$50||$62.50||$67.50||$131.50|
Rabi Murad, Ph.D.
Director, Bioinformatics Shared Resource
(858) 795-5200 ext. 4008
Dr. Rabi Murad specializes in applying integrative genomics and epigenomics techniques for biomarker discovery in developmental biology, microRNA biology, and cancer. He has contributed to diverse projects such as genome/transcriptome assembly, functional annotation, gene expression profiling including at single cell level, microRNA profiling, and epigenomics profiling such as ChIP-seq and ATAC-seq. Dr. Murad received his Ph.D. in biological sciences from University of California Irvine, where he received extensive training in applying genomics and bioinformatics techniques to diverse questions in developmental biology and cancer. As part of the ENCODE consortium, his work led to near comprehensive profiling and characterization of microRNAs during mouse embryonic development. He has contributed to several scientific papers published in prominent genome biology journals such as Genome Research and BMC Genomics as well as in Science and Nature.
Email Rabi Murad
Yuk-Lap (Kevin) Yip, Ph.D.
Email Kevin Yip
Please call (858) 795-5200 ext. 5085 or use the button below to send us an email.