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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
  • Genetics, genes, genome, genetic risk … Such terms are becoming increasingly familiar to even nonresearchers as studies and information about the human make-up become more extensive and more critical. At City of Hope, these words have long been part of our vocabulary. Researchers and physicians are studyi...
  • Mammograms are currently the best method to detect breast cancer early, when it’s easier to treat and before it’s big enough to feel or cause symptoms. But recent mammogram screening guidelines may have left some women confused about when to undergo annual testing. Here Lusi Tumyan, M.D., chief of t...
  • Although chemotherapy can be effective in treating cancer, it can also exact a heavy toll on a patient’s health. One impressive alternative researchers have found is in the form of a vaccine. A type of immunotherapy, one part of the vaccine primes the body to react strongly against a tumor; the second part dire...
  • The breast cancer statistic is attention-getting: One in eight women will be diagnosed with breast cancer during her lifetime. That doesn’t mean that, if you’re one of eight women at a dinner table, one of you is fated to have breast cancer (read more on that breast cancer statistic), but it does mean that the ...
  • Rob Darakjian was diagnosed with acute lymphoblastic leukemia at just 19 years old. He began chemotherapy and was in and out of the hospital for four months. After his fourth round of treatment, he received a bone marrow transplantation from an anonymous donor. Today, he’s cancer free. In his first post, ...
  • Advanced age tops the list among breast cancer risk factor for women. Not far behind is family history and genetics. Two City of Hope researchers delving deep into these issues recently received important grants to advance their studies. Arti Hurria, M.D., director of the Cancer and Aging Research Program, and ...
  • City of Hope is extending the reach of its lifesaving mission well beyond U.S. borders. To that end, three distinguished City of Hope leaders visited China earlier this year to lay the foundation for the institution’s new International Medicine Program. The program is part of City of Hope’s strategi...
  • A hallmark of cancer is that it doesn’t always limit itself to a primary location. It spreads. Breast cancer and lung cancer in particular are prone to spread, or metastasize, to the brain. Often the brain metastasis isn’t discovered until years after the initial diagnosis, just when patients were beginning to ...
  • Blueberries, cinnamon, baikal scullcap, grape seed extract (and grape skin extract), mushrooms, barberry, pomegranates … all contain compounds with the potential to treat, or prevent, cancer. Scientists at City of Hope have found tantalizing evidence of this potential and are determined to explore it to t...
  • Most women who are treated for breast cancer with a mastectomy do not choose to undergo reconstructive surgery. The reasons for this, according to a recent JAMA Surgery study, vary. Nearly half say they do not want any additional surgery, while nearly 34 percent say breast cancer reconstruction simply isn’t imp...
  • The leading risk factor for breast cancer is simply being a woman. The second top risk factor is getting older. Obviously, these two factors cannot be controlled, which is why all women should be aware of their risk and how to minimize those risks. Many risk factors can be mitigated, and simple changes can lead...
  • All women are at some risk of developing the disease in their lifetimes, but breast cancer, like other cancers, has a disproportionate effect on minorities. Although white women have the highest incidence of breast cancer, African-American women have the highest breast cancer death rates of all racial and ethni...
  • First, the good news: HIV infections have dropped dramatically over the past 30 years. Doctors, researchers and health officials have made great strides in preventing and treating the disease, turning what was once a death sentence into, for some, a chronic condition. Now, the reality check: HIV is still a worl...
  • Screening for breast cancer has dramatically increased the number of cancers found before they cause symptoms – catching the disease when it is most treatable and curable. Mammograms, however, are not infallible. It’s important to conduct self-exams, and know the signs and symptoms that should be checked by a h...
  • Rob Darakjian was diagnosed with acute lymphoblastic leukemia at just 19 years old. He began chemotherapy and was in and out of the hospital for four months. After his fourth round of treatment, he received a bone marrow transplantation from an anonymous donor. Today, he’s cancer free.   In his previ...