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Bioinformatics Core (BIC) Facility Bookmark and Share

Bioinformatics Core (BIC) Facility

City of Hope’s Bioinformatics Core (BIC) Facility provides researchers with high-throughput biological data analysis tools, data management, unified cyber-infrastructure, training, as well as trained staff working with multidisciplinary team to facilitate experimental design, information management, data integration, annotation, dissemination and visualization. Our goal is to foster collaborations and provide high-performance parallel computational support for principle investigators and develop modern computational techniques and methodologies for their basic and translational research.

The facilities and their services are available to both City of Hope and non-City of Hope researchers to include in their grant proposals for adequate chargeback.
 
The Bioinformatics Core Facility provides support in the following areas:
 
 
  1. Image Analysis Resources: The BIC provides data analysis and data management support for both the Sequencing Core and individual researchers for Illumina Solexa and Roche/454 as well as for sequence data generated from ABI sequencers.
  2. Microarray Analysis: The BIC provides statistical analysis and biological interpretation for microarray data as well as data integration for various array types.  BIC is also building a microarray database from open-source gene expression data. 
  3. Computer-Assisted Molecular Design Resources: The BIC conducts computer-assisted molecular design analysis, performs 3D structure analysis of protein/DNA/RNA and their drug complexes, and provides large compound libraries and similarity queries for drug discovery.
  4. Molecular Imaging Analysis: The BIC plans to expand services offered to cover imaging analysis (e.g. microscopy analysis, quantification of reporter genes, etc.).
  5. LIMS: The BIC offers Laboratory Information Management Systems (LIMS) for Next-Generation-Sequencing (CBIS), Microarray (caArray), and High-Throughput Screening (CBIS) data.
  6. Software Support: The BIC encourages users to conduct their own analysis, and provides useful software via Citrix and local installation on BIC workstations.  Training sessions are offered for available software and post tutorials/FAQs are posted on the BIC wiki.  BIC also designs high performance cyber-infrastructure and analysis pipelines to automate the collections of experimental information.
  7. Ad hoc Software Development: The BIC develops new tools for users (such as the ArrayTools R package, SeqGene analysis software, the Similarity Search Pipeline, and the siRNA Site Selector).
 
Please contact Yate-Ching Yuan - yyuan@coh.org - for any questions, help requests, feedback, or ad hoc support.
 

Research reported in this publication included work performed in the Bioinformatics Core supported by the National Cancer Institute of the National Institutes of Health under award number P30CA33572. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
 

Genomic Analysis Resources

  • Analyze data provided by the Functional Genomics Core
     
  • Develop semi-automated analysis pipelines in order to provide more efficient support.
     
  • Build a database of open source microarray data that will allow users to analyze associations between genes and clinical variables (stage, age, survival, etc.)
     
  • Provide consultation, interpretation, and visualization of analysis results
     
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines.
     
  • Provide software (such as Partek, IPA, etc.) to assist users with their own analysis
The following types of microarray analysis are currently supported:
 
  1. Gene Expression Profiling
     
  2. miRNA Profiling
     
  3. DNA Methylation Array Analysis
     
  4. Exon Splicing Array Analysis
     
  5. Tiling Array Analysis - Includes ChIP-ChIP
     
  6. CGH Array Analysis (Copy Number Analysis)
     
  7. Drug Metabolism Analysis (DMET array)
     
  8. Pathway analysis and functional interpretation
 

Image Analysis Resources

  • Perform QC for data collected at the Sequencing Core.
     
  • Provide support for data pre-processing, including adapter trimming, bar code trimming, sequence alignment and data format conversion so that the Solexa user can easily visualize NGS sequencing data using IGV and other software.
     
  • Develop semi-automated Solexa analysis pipelines to provide more efficient support.
     
  • Provide consultation, interpretation, and visualization of analysis results.
     
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines.
     
  • Provide software (such as Partek, NextGENe, etc.) to assist users with their own analysis.
The following types of sequence analysis are currently supported:
 
  1. mall RNA-seq, including expression level of small RNAs (including miRNA and other non-coding RNAs), detection of novel small RNAs, prediction of novel miRNA precursors and differential expression analysis.
     
  2. DNA-Seq, mainly for copy number analysis.
     
  3. Targeted resequencing (e.g. exome sequencing, PCR amplicon sequencing), including variants detection, small and large indel detection, and structural variation.
     
  4. RNA-seq, including peak detection, motif analysis, and more advanced analysis.
     
  5. ChIP-seq, including peak detection, motif analysis, and more advanced analysis
     
  6. For other data types, consult the BIC staff.
 

Computer-Assisted Molecular Design Resources

  • Structural/functional analysis for disease related biological process
  • Computer-aided therapeutic discovery and development
  • Provide the High-Throughput Screening Core with data analysis and data management assistance.
  • Provide consultation, interpretation, and visualization of analysis results
  • Develop novel tools for analysis
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines
  • Provide software (such as PyMol, NAMD, etc.) to assist users with their own analysis
The following types of drug-discovery initiatives are currently supported:
 
  1. Biomarker Analysis: An in depth understanding and analysis of the biological functions and 3D structural relationships of therapeutic targets (protein, small RNA, organic compounds) are essential for understanding the molecular mechanisms and binding modes of these tertiary complex interactions. Virtual screening can be performed on the 3D structure and binding sites based on the X-ray structure and/or predicted homology model.  Ligand-based virtual screening can be performed by 2D and/or 3D tools (developed in house) as well as the compounds library database to find analogues among more than 15 million drug-like compounds.
     
  2. Chemical Library Preparation: The drug candidates are screened from a collection of chemical libraries that the BIC core has collected.  Millions of compounds from various commercial and public libraries have been integrated.  The BIC core also filters HTS results based on HTS and ADMET requirements to help reduce the redundancy, as well as false positive and false negative hits.
     
  3. Lead Identification: Structure-based or ligand-based virtual screening is conducted, as well as 2D/3D structure similarity compound searches among several million candidates from the NCI DTP, UCSF ZINC, NCBI Pubmed and COH HTS compound libraries.
     
  4. Lead Optimization: The lead compounds are further optimized by computational chemistry methods such as Molecular Dynamic Simulation and QSAR analysis.
     
  5. Pre-clinical Trial: The drug candidates obtained from the virtual screenings are readied by the investigator for pre-clinical trials.  The experimental results are then fed back through the drug-design process for drug refinement.
 

Software / Equipment

BIC Software (on Citrix)
  • Programs for Image Analysis: Biobase TRANSFAC, CLC Bio Genomics Workbench, CLC Bio Main Workbench, DMET Console, IGV, Labshare, NextGene, Oligo, R, Seqlab, Sequence Alignment, Sequencer, SeqWeb 3, Vector NTI (Version 10 and 11)
  • Genomic Analysis:  Ingenuity Pathway Analysis, Biobase TRANSFAC, Cluster 3.0, GeneSpring 7.3, GeneSpring GX, IGV, ImaGene, Matlab, Oligo, Partek, R, Signal Map
  • Computer-Assisted Molecular Design: Cn3D, COH Similarity Pipeline, Discovery Studio, DS Viewer Pro, HyperChem 7.5, Matlab, Pymol, R, Rasmol, Swiss PDB Viewer
  • DCT: CBIS, Biocore T100 Evaluation, Chem4D Draw, and HyperChem 7.5 DCT
  • A limited number of programs are not available on Citrix: contact Yate-Ching Yuan, Ph.D. at yyuan@coh.org for more details
 
BIC Workstations
  • Commonly used bioinformatics programs are also installed on 9 BIC workstations located in computer rooms throughout the campus and in the Flower building.  Contact Yate-Ching Yuan, Ph.D. at yyuan@coh.org for the locations and policies of BIC workstations.
 
Computational Resources
  • scaleMP - Cyberinfrastructure utilizes the latest blade system technology and ScaleMP's Versatile SMP (vSMP) Foundation technology to deliver a scalable computation solution. The computational resources of the Cyberinfrastructure compose a scaleMP vSMP system with 32 core and 128GB memory, high performance database servers, and high performance MS Windows/Linux application servers.
  • Isilon Tired Storage Cluster solutions – 143 TB of data for storing results from high-throughput sequencing, high-throughput screening, and microarray results.
  • A large number of different servers are utilized to meet users’ needs. Contact Yate-Ching Yuan, Ph.D. at yyuan@coh.org for details.

Using the Facility

Image Analysis Resources
  • Contact Harry Gao from the DNA Sequencing/Solexa Core and Xiwei Wu or Xutao Deng from the BIC to ensure optimal experimental design.
 
  • When the DNA Sequencing/Solexa Core completes a sequencing run the data will be directly piped to the BIC staff unless instructed otherwise.
 
  • The turn-around time will vary depending on the complexity of the project. The turn-around time for most applications is 2-3 weeks. For novel applications, the turn-around time may be up to 3-4 weeks.
 
  • The BIC does not typically support analyzing public domain sequencing data.
 
  • Contact Haiqing Li if support is needed on LIMS, database, software or hardware issues related to sequencing.

Genomic Analysis Resources
  • The BIC analyzes microarray data produced by the Functional Genomics Core. The turn-around time (after receiving the raw data from the Functional Genomics Core) is typically 2-3 weeks.
 
  • The BIC also provides some data mining of publicly available datasets on a case-by-case basis.  Contact Yate-Ching Yuan (yyuan@coh.org) for more information.

Computer-Assisted Molecular Design Resources
Contact Yate-Ching Yuan to set up a project planning meeting for the purpose of assembling team collaborations from other Cores as needed.
 

Abstract for Grants

City of Hope’s Bioinformatics Core (BIC) facility provides researchers with high-throughput biological data analysis tools, data management, unified cyber-infrastructure, training, as well as trained staff working within  multidisciplinary teams to facilitate experimental design, information management, data integration, annotation, dissemination and visualization. Our goal is to foster collaborations and provide high-performance parallel computational support for principle investigators and develop modern computational techniques and methods for their basic and translational research.
 
Image Analysis Resources
BIC will support CPU/memory intensive parallel computation for Smith-Waterman alignment algorithm on GPU using CUDA sequence alignment, BLAST/BLAT/BioMart database search, MEM motif prediction, MFOLD RNA folding, and sequence contig assembly analysis etc. Invitrogen Labshare Oracle based data management is provided for Vector NTI sequence analysis, MacVector, GeneCode Sequencher, CLC Bio Workbench, TRANSFAC gene transcription factor database, as well as open source NCBI BLAST, BLAT services, Oligo design, UCSC local mirror site with human and mouse database, Broad IGV, and Mathwork Matlab statistical and bioinformatics tool kits.
 
BIC will support statistical and computational analysis for image preprocessing, base calling, sequence alignment, and down-stream analysis of DNA-Seq, ChIP-seq, Methyl-seq, mRNA-seq, smRNA-seq, targeted resequencing, RNA-seq.  BIC currently hosts commercial Illumina Solexa GA II pipeline and CASAVA, Roche 454 , vendor based NGS analysis software from SoftGenetics NextGENe, and Partek Genomics Suite, as well as several academic open source software products such as local mirror site of UCSC Genome browser, Blat, SOAP, MAQ, BWA, Bowtie, Novoalign, Samtools, R/Bioconductor, LIMS such as SeqWare and CBIS. BIC also developed accelerated Smith-Waterman alignment algorithm on GPU using CUDA for supporting efficient Solexa genome-wide alignment which will accommodate large indels and abundant structural variations, as well as SeqGene for Exome and transcritomic open source NGS analysis. BIC also provides training workshops for Partek, NextGENe, NCBI, Ensemble, BioMart, UCSC genome browser, and Broad IGV etc.
 
Genomic Analysis Resources
BIC will support statistical and computational programs for microarray image preprocessing, generating differential expression profiling for biomarkers, down-stream analysis for expression, copy number, miRNA, ChIP-ChIP analysis, as well as integrated genomic analysis. BIC currently hosts comprehensive commercial microarray software from Affymetrix, Agilent, NimbleGen, Exiqon, BioDiscovery, Nexus, Partek Genomics Suite, Agilent GeneSpring, Ingenuity as well as many academic open source software such as local mirror site of UCSC Genome browser, Blat, Biobase TRANSFAC, Gene Cluster, and R/Bioconductor, etc. We also provide user training workshops for Partek, GeneSpring, NCBI, Ensemble, BioMart, and UCSC genome browser etc.
 
Computer-Assisted Molecular Design Resources
BIC can provide a structure based virtual ligand screening (VLS) approach to identify potential leads against the X-ray crystal structure and/or homology models of potential ligand binding sites that were predicted. BIC can provide the qualitative assessment for virtual mutagenesis experiments to predict the structural activity relationships and then compare with bioassay results. BIC offers molecular dynamic simulation of these protein-ligand complex structures as well as their association constants as confirmation of the docking strategy. BIC can also design a highly diverse HTS compound library available for robotic screening based on approximately 15 million compounds downloaded from NCBI PubChem, as well as  several thousand natural compound libraries. BIC can correlate binding affinity and IC50 of potential ligands to perform CoMFA and QSAR analysis to assist medicinal chemistry to optimize potential leads. BIC can also perform ADMET analysis for the prediction of toxicity and metabolomic predictions to develop drugable compounds for clinical trials. BIC currently hosts comprehensive commercial modeling software from Tripos, Schrodinger, SimulationPlus, Chemiinovation, academic software AMBER, Charmm, MOPAC, as well as compound libraries from NCBI, UCSF ZINC, and several pharmaceutical companies such as Chambridge, ChemDiv, etc. User training workshops are conducted for NCBI, TRIPOS, Schrodinger, Ensemble.
 

Bioinformatics Core Team

Contact Us

Yate-Ching Yuan, Ph.D.
Associate Research Professor
Director,
Bioinformatics Core Facility
yyuan@coh.org
626-256-HOPE (4673)
ext. 62161

Xiwei Wu, Ph.D.
Assistant Research Professor
Associate Director,
Bioinformatics Core Facility
xwu@coh.org
626-256-HOPE (4673)
ext. 65071

Zheng Liu, Ph.D.
Assistant Research Professor
Manager,
Bioinformatics Core Facility
zliu@coh.org
626-256-HOPE (4673)
ext. 65170

Hongzhi Li, Ph.D.
Assistant Research Professor
hongzhili@coh.org
626-256-HOPE (4673)
ext.60219

Leila Su, Ph.D.
Assistant Research Professor
lsu@coh.org
626-256-HOPE (4673)
ext. 63753

Haiqing Li, Ph.D.
Staff Scientist
hali@coh.org
626-256-HOPE (4673)
ext. 63653

Charles Warden, M.A.
BioinformaticsSpecialist
cwarden@coh.org
626-256-HOPE (4673)
ext. 60233

Bing Mu, M.S.
Bioinformatics Specialist
bmu@coh.org
626-256-HOPE (4673)
ext. 60553

Sue Hargrave, B.A.
Project Coordinator
shargrave@coh.org
626-256-HOPE (4673)
ext. 64275

 

 

Bioinformatics Core (BIC) Facility

Bioinformatics Core (BIC) Facility

City of Hope’s Bioinformatics Core (BIC) Facility provides researchers with high-throughput biological data analysis tools, data management, unified cyber-infrastructure, training, as well as trained staff working with multidisciplinary team to facilitate experimental design, information management, data integration, annotation, dissemination and visualization. Our goal is to foster collaborations and provide high-performance parallel computational support for principle investigators and develop modern computational techniques and methodologies for their basic and translational research.

The facilities and their services are available to both City of Hope and non-City of Hope researchers to include in their grant proposals for adequate chargeback.
 
The Bioinformatics Core Facility provides support in the following areas:
 
 
  1. Image Analysis Resources: The BIC provides data analysis and data management support for both the Sequencing Core and individual researchers for Illumina Solexa and Roche/454 as well as for sequence data generated from ABI sequencers.
  2. Microarray Analysis: The BIC provides statistical analysis and biological interpretation for microarray data as well as data integration for various array types.  BIC is also building a microarray database from open-source gene expression data. 
  3. Computer-Assisted Molecular Design Resources: The BIC conducts computer-assisted molecular design analysis, performs 3D structure analysis of protein/DNA/RNA and their drug complexes, and provides large compound libraries and similarity queries for drug discovery.
  4. Molecular Imaging Analysis: The BIC plans to expand services offered to cover imaging analysis (e.g. microscopy analysis, quantification of reporter genes, etc.).
  5. LIMS: The BIC offers Laboratory Information Management Systems (LIMS) for Next-Generation-Sequencing (CBIS), Microarray (caArray), and High-Throughput Screening (CBIS) data.
  6. Software Support: The BIC encourages users to conduct their own analysis, and provides useful software via Citrix and local installation on BIC workstations.  Training sessions are offered for available software and post tutorials/FAQs are posted on the BIC wiki.  BIC also designs high performance cyber-infrastructure and analysis pipelines to automate the collections of experimental information.
  7. Ad hoc Software Development: The BIC develops new tools for users (such as the ArrayTools R package, SeqGene analysis software, the Similarity Search Pipeline, and the siRNA Site Selector).
 
Please contact Yate-Ching Yuan - yyuan@coh.org - for any questions, help requests, feedback, or ad hoc support.
 

Research reported in this publication included work performed in the Bioinformatics Core supported by the National Cancer Institute of the National Institutes of Health under award number P30CA33572. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
 

Genomic Analysis Resources

Genomic Analysis Resources

  • Analyze data provided by the Functional Genomics Core
     
  • Develop semi-automated analysis pipelines in order to provide more efficient support.
     
  • Build a database of open source microarray data that will allow users to analyze associations between genes and clinical variables (stage, age, survival, etc.)
     
  • Provide consultation, interpretation, and visualization of analysis results
     
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines.
     
  • Provide software (such as Partek, IPA, etc.) to assist users with their own analysis
The following types of microarray analysis are currently supported:
 
  1. Gene Expression Profiling
     
  2. miRNA Profiling
     
  3. DNA Methylation Array Analysis
     
  4. Exon Splicing Array Analysis
     
  5. Tiling Array Analysis - Includes ChIP-ChIP
     
  6. CGH Array Analysis (Copy Number Analysis)
     
  7. Drug Metabolism Analysis (DMET array)
     
  8. Pathway analysis and functional interpretation
 

Image Analysis Resources

Image Analysis Resources

  • Perform QC for data collected at the Sequencing Core.
     
  • Provide support for data pre-processing, including adapter trimming, bar code trimming, sequence alignment and data format conversion so that the Solexa user can easily visualize NGS sequencing data using IGV and other software.
     
  • Develop semi-automated Solexa analysis pipelines to provide more efficient support.
     
  • Provide consultation, interpretation, and visualization of analysis results.
     
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines.
     
  • Provide software (such as Partek, NextGENe, etc.) to assist users with their own analysis.
The following types of sequence analysis are currently supported:
 
  1. mall RNA-seq, including expression level of small RNAs (including miRNA and other non-coding RNAs), detection of novel small RNAs, prediction of novel miRNA precursors and differential expression analysis.
     
  2. DNA-Seq, mainly for copy number analysis.
     
  3. Targeted resequencing (e.g. exome sequencing, PCR amplicon sequencing), including variants detection, small and large indel detection, and structural variation.
     
  4. RNA-seq, including peak detection, motif analysis, and more advanced analysis.
     
  5. ChIP-seq, including peak detection, motif analysis, and more advanced analysis
     
  6. For other data types, consult the BIC staff.
 

Computer-Assisted Molecular Design Resources

Computer-Assisted Molecular Design Resources

  • Structural/functional analysis for disease related biological process
  • Computer-aided therapeutic discovery and development
  • Provide the High-Throughput Screening Core with data analysis and data management assistance.
  • Provide consultation, interpretation, and visualization of analysis results
  • Develop novel tools for analysis
  • Create laboratory information management systems (LIMS) for sample and experiment inventory as well as automated data pre-processing pipelines
  • Provide software (such as PyMol, NAMD, etc.) to assist users with their own analysis
The following types of drug-discovery initiatives are currently supported:
 
  1. Biomarker Analysis: An in depth understanding and analysis of the biological functions and 3D structural relationships of therapeutic targets (protein, small RNA, organic compounds) are essential for understanding the molecular mechanisms and binding modes of these tertiary complex interactions. Virtual screening can be performed on the 3D structure and binding sites based on the X-ray structure and/or predicted homology model.  Ligand-based virtual screening can be performed by 2D and/or 3D tools (developed in house) as well as the compounds library database to find analogues among more than 15 million drug-like compounds.
     
  2. Chemical Library Preparation: The drug candidates are screened from a collection of chemical libraries that the BIC core has collected.  Millions of compounds from various commercial and public libraries have been integrated.  The BIC core also filters HTS results based on HTS and ADMET requirements to help reduce the redundancy, as well as false positive and false negative hits.
     
  3. Lead Identification: Structure-based or ligand-based virtual screening is conducted, as well as 2D/3D structure similarity compound searches among several million candidates from the NCI DTP, UCSF ZINC, NCBI Pubmed and COH HTS compound libraries.
     
  4. Lead Optimization: The lead compounds are further optimized by computational chemistry methods such as Molecular Dynamic Simulation and QSAR analysis.
     
  5. Pre-clinical Trial: The drug candidates obtained from the virtual screenings are readied by the investigator for pre-clinical trials.  The experimental results are then fed back through the drug-design process for drug refinement.
 

Software / Equipment

Software / Equipment

BIC Software (on Citrix)
  • Programs for Image Analysis: Biobase TRANSFAC, CLC Bio Genomics Workbench, CLC Bio Main Workbench, DMET Console, IGV, Labshare, NextGene, Oligo, R, Seqlab, Sequence Alignment, Sequencer, SeqWeb 3, Vector NTI (Version 10 and 11)
  • Genomic Analysis:  Ingenuity Pathway Analysis, Biobase TRANSFAC, Cluster 3.0, GeneSpring 7.3, GeneSpring GX, IGV, ImaGene, Matlab, Oligo, Partek, R, Signal Map
  • Computer-Assisted Molecular Design: Cn3D, COH Similarity Pipeline, Discovery Studio, DS Viewer Pro, HyperChem 7.5, Matlab, Pymol, R, Rasmol, Swiss PDB Viewer
  • DCT: CBIS, Biocore T100 Evaluation, Chem4D Draw, and HyperChem 7.5 DCT
  • A limited number of programs are not available on Citrix: contact Yate-Ching Yuan, Ph.D. at yyuan@coh.org for more details
 
BIC Workstations
  • Commonly used bioinformatics programs are also installed on 9 BIC workstations located in computer rooms throughout the campus and in the Flower building.  Contact Yate-Ching Yuan, Ph.D. at yyuan@coh.org for the locations and policies of BIC workstations.
 
Computational Resources
  • scaleMP - Cyberinfrastructure utilizes the latest blade system technology and ScaleMP's Versatile SMP (vSMP) Foundation technology to deliver a scalable computation solution. The computational resources of the Cyberinfrastructure compose a scaleMP vSMP system with 32 core and 128GB memory, high performance database servers, and high performance MS Windows/Linux application servers.
  • Isilon Tired Storage Cluster solutions – 143 TB of data for storing results from high-throughput sequencing, high-throughput screening, and microarray results.
  • A large number of different servers are utilized to meet users’ needs. Contact Yate-Ching Yuan, Ph.D. at yyuan@coh.org for details.

Bioinformatics Core (BIC) Facility Using the Facility

Using the Facility

Image Analysis Resources
  • Contact Harry Gao from the DNA Sequencing/Solexa Core and Xiwei Wu or Xutao Deng from the BIC to ensure optimal experimental design.
 
  • When the DNA Sequencing/Solexa Core completes a sequencing run the data will be directly piped to the BIC staff unless instructed otherwise.
 
  • The turn-around time will vary depending on the complexity of the project. The turn-around time for most applications is 2-3 weeks. For novel applications, the turn-around time may be up to 3-4 weeks.
 
  • The BIC does not typically support analyzing public domain sequencing data.
 
  • Contact Haiqing Li if support is needed on LIMS, database, software or hardware issues related to sequencing.

Genomic Analysis Resources
  • The BIC analyzes microarray data produced by the Functional Genomics Core. The turn-around time (after receiving the raw data from the Functional Genomics Core) is typically 2-3 weeks.
 
  • The BIC also provides some data mining of publicly available datasets on a case-by-case basis.  Contact Yate-Ching Yuan (yyuan@coh.org) for more information.

Computer-Assisted Molecular Design Resources
Contact Yate-Ching Yuan to set up a project planning meeting for the purpose of assembling team collaborations from other Cores as needed.
 

Abstract for Grants

Abstract for Grants

City of Hope’s Bioinformatics Core (BIC) facility provides researchers with high-throughput biological data analysis tools, data management, unified cyber-infrastructure, training, as well as trained staff working within  multidisciplinary teams to facilitate experimental design, information management, data integration, annotation, dissemination and visualization. Our goal is to foster collaborations and provide high-performance parallel computational support for principle investigators and develop modern computational techniques and methods for their basic and translational research.
 
Image Analysis Resources
BIC will support CPU/memory intensive parallel computation for Smith-Waterman alignment algorithm on GPU using CUDA sequence alignment, BLAST/BLAT/BioMart database search, MEM motif prediction, MFOLD RNA folding, and sequence contig assembly analysis etc. Invitrogen Labshare Oracle based data management is provided for Vector NTI sequence analysis, MacVector, GeneCode Sequencher, CLC Bio Workbench, TRANSFAC gene transcription factor database, as well as open source NCBI BLAST, BLAT services, Oligo design, UCSC local mirror site with human and mouse database, Broad IGV, and Mathwork Matlab statistical and bioinformatics tool kits.
 
BIC will support statistical and computational analysis for image preprocessing, base calling, sequence alignment, and down-stream analysis of DNA-Seq, ChIP-seq, Methyl-seq, mRNA-seq, smRNA-seq, targeted resequencing, RNA-seq.  BIC currently hosts commercial Illumina Solexa GA II pipeline and CASAVA, Roche 454 , vendor based NGS analysis software from SoftGenetics NextGENe, and Partek Genomics Suite, as well as several academic open source software products such as local mirror site of UCSC Genome browser, Blat, SOAP, MAQ, BWA, Bowtie, Novoalign, Samtools, R/Bioconductor, LIMS such as SeqWare and CBIS. BIC also developed accelerated Smith-Waterman alignment algorithm on GPU using CUDA for supporting efficient Solexa genome-wide alignment which will accommodate large indels and abundant structural variations, as well as SeqGene for Exome and transcritomic open source NGS analysis. BIC also provides training workshops for Partek, NextGENe, NCBI, Ensemble, BioMart, UCSC genome browser, and Broad IGV etc.
 
Genomic Analysis Resources
BIC will support statistical and computational programs for microarray image preprocessing, generating differential expression profiling for biomarkers, down-stream analysis for expression, copy number, miRNA, ChIP-ChIP analysis, as well as integrated genomic analysis. BIC currently hosts comprehensive commercial microarray software from Affymetrix, Agilent, NimbleGen, Exiqon, BioDiscovery, Nexus, Partek Genomics Suite, Agilent GeneSpring, Ingenuity as well as many academic open source software such as local mirror site of UCSC Genome browser, Blat, Biobase TRANSFAC, Gene Cluster, and R/Bioconductor, etc. We also provide user training workshops for Partek, GeneSpring, NCBI, Ensemble, BioMart, and UCSC genome browser etc.
 
Computer-Assisted Molecular Design Resources
BIC can provide a structure based virtual ligand screening (VLS) approach to identify potential leads against the X-ray crystal structure and/or homology models of potential ligand binding sites that were predicted. BIC can provide the qualitative assessment for virtual mutagenesis experiments to predict the structural activity relationships and then compare with bioassay results. BIC offers molecular dynamic simulation of these protein-ligand complex structures as well as their association constants as confirmation of the docking strategy. BIC can also design a highly diverse HTS compound library available for robotic screening based on approximately 15 million compounds downloaded from NCBI PubChem, as well as  several thousand natural compound libraries. BIC can correlate binding affinity and IC50 of potential ligands to perform CoMFA and QSAR analysis to assist medicinal chemistry to optimize potential leads. BIC can also perform ADMET analysis for the prediction of toxicity and metabolomic predictions to develop drugable compounds for clinical trials. BIC currently hosts comprehensive commercial modeling software from Tripos, Schrodinger, SimulationPlus, Chemiinovation, academic software AMBER, Charmm, MOPAC, as well as compound libraries from NCBI, UCSF ZINC, and several pharmaceutical companies such as Chambridge, ChemDiv, etc. User training workshops are conducted for NCBI, TRIPOS, Schrodinger, Ensemble.
 

Bioinformatics Core Team

Bioinformatics Core Team

Contact Us

Contact Us

Yate-Ching Yuan, Ph.D.
Associate Research Professor
Director,
Bioinformatics Core Facility
yyuan@coh.org
626-256-HOPE (4673)
ext. 62161

Xiwei Wu, Ph.D.
Assistant Research Professor
Associate Director,
Bioinformatics Core Facility
xwu@coh.org
626-256-HOPE (4673)
ext. 65071

Zheng Liu, Ph.D.
Assistant Research Professor
Manager,
Bioinformatics Core Facility
zliu@coh.org
626-256-HOPE (4673)
ext. 65170

Hongzhi Li, Ph.D.
Assistant Research Professor
hongzhili@coh.org
626-256-HOPE (4673)
ext.60219

Leila Su, Ph.D.
Assistant Research Professor
lsu@coh.org
626-256-HOPE (4673)
ext. 63753

Haiqing Li, Ph.D.
Staff Scientist
hali@coh.org
626-256-HOPE (4673)
ext. 63653

Charles Warden, M.A.
BioinformaticsSpecialist
cwarden@coh.org
626-256-HOPE (4673)
ext. 60233

Bing Mu, M.S.
Bioinformatics Specialist
bmu@coh.org
626-256-HOPE (4673)
ext. 60553

Sue Hargrave, B.A.
Project Coordinator
shargrave@coh.org
626-256-HOPE (4673)
ext. 64275

 

 
Research Shared Services

City of Hope embodies the spirit of scientific collaboration by sharing services and core facilities with colleagues here and around the world.
 

Recognized nationwide for its innovative biomedical research, City of Hope's Beckman Research Institute is home to some of the most tenacious and creative minds in science.
City of Hope is one of only 41 Comprehensive Cancer Centers in the country, the highest designation awarded by the National Cancer Institute to institutions that lead the way in cancer research, treatment, prevention and professional education.
Learn more about City of Hope's institutional distinctions, breakthrough innovations and collaborations.
Support Our Research
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NEWS & UPDATES
  • Equipping the immune system to fight cancer – a disease that thrives on mutations and circumventing the body’s natural defenses – is within reach. In fact, City of Hope researchers are testing one approach in clinical trials now. Scientists take a number of steps to turn cancer patients’ T cells – white b...
  • As treatments for lung cancer become more targeted and effective, the need for better technology to detect lung cancer mutations becomes increasingly important. A new clinical study at City of Hope is examining the feasibility of using blood and urine tests to detect lung cancer mutations, potentially allowing ...
  • When it comes to breast cancer risk, insulin levels may matter more than weight, new research has found. The study from Imperial College London School of Public Health, published in the journal Cancer Research, indicates that metabolic health – not a person’s weight or body mass index – increases breast cancer ...
  • No one ever plans to have cancer – and there’s never a good time. For Homa Sadat, her cancer came at a particularly bad time: just one year after losing her father to the pancreatic cancer he had battled for two years. She was working a grueling schedule managing three commercial office buildings. She’d just [&...
  • Patients at City of Hope – most of whom are fighting cancer – rely on more than 37,000 units of blood and platelets each year for their treatment and survival. Every one of those units comes from family, friends or someone who traded an hour or so of their time and a pint of their […]
  • Surgery is vital in the treatment of cancer – it’s used to help diagnose, treat and even prevent the disease – so a new colorectal cancer study linking a decrease in surgeries for advanced cancer to increased survival rates may raise more questions than it answers for some patients. The surgery-and-surviv...
  • Age is the single greatest risk factor overall for cancer; our chances of developing the disease rise steeply after age 50. For geriatric oncology nurse Peggy Burhenn, the meaning is clear: Cancer is primarily a geriatric condition. That’s why she is forging inroads in the care of older adults with cancer. Burh...
  • One of American’s great sportscasters, Stuart Scott, passed away from recurrent cancer of the appendix at the young age of 49. His cancer was diagnosed when he was only 40 years old. It was found during an operation for appendicitis. His courageous fight against this disease began in 2007, resumed again with an...
  • When Homa Sadat found a lump in her breast at age 27, her gynecologist told her what many doctors say to young women: You’re too young to have breast cancer. With the lump dismissed as a harmless cyst, she didn’t think about it again until she was at a restaurant six months later and felt […]
  • What most people call a “bone marrow transplant” is not actually a transplant of bone marrow; it is instead the transplantation of what’s known as hematopoietic stem cells. Such cells are often taken from bone marrow, but not always. Hematopoietic stem cells are simply immature cells that can ...
  • Doctors have long known that women with a precancerous condition called atypical hyperplasia have an elevated risk of breast cancer. Now a new study has found that the risk is more serious than previously thought. Hyperplasia itself is an overgrowth of cells; atypical hyperplasia is an overgrowth in a distorted...
  • Don’t kid yourself. Just because it’s mid-January doesn’t mean it’s too late to make resolutions for a happier, and healthier, 2015. Just consider them resolutions that are more mature than those giddy, sometimes self-deluded, Jan. 1 resolutions. To that end, we share some advice from Cary A. Presant, M.D., an ...
  • Sales and marketing executive Jim Murphy first came to City of Hope in 2002 to donate blood for a friend who was being treated for esophageal cancer. The disease is serious. Although esophageal cancer accounts for only about 1 percent of cancer diagnoses in the U.S., only about 20 percent of patients survive at...
  • Aaron Bomar and his family were celebrating his daughter’s 33rd birthday in September 2014 when he received alarming news: According to an X-ray taken earlier that day at an urgent care facility, he had a node on his aorta and was in danger of an aneurysm. Bomar held hands with his wife and daughter and s...
  • Explaining a prostate cancer diagnosis to a young child can be difficult — especially when the cancer is incurable. But conveying the need for prostate cancer research, as it turns out, is easily done. And that leads to action. Earlier this year, Gerald Rustad, 71, who is living with a very aggressive form of m...