A New Oklahoma Bioinformatics Company. Microarray and Bioinformatics.

Slides:



Advertisements
Similar presentations
Recombinant DNA Technology
Advertisements

BiGCaT Bioinformatics Hunting strategy of the bigcat.
Bioinformatics at WSU Matt Settles Bioinformatics Core Washington State University Wednesday, April 23, 2008 WSU Linux User Group (LUG)‏
1 MicroArray -- Data Analysis Cecilia Hansen & Dirk Repsilber Bioinformatics - 10p, October 2001.
Gene expression analysis summary Where are we now?
Microarrays Dr Peter Smooker,
Bioinformatics: a Multidisciplinary Challenge Ron Y. Pinter Dept. of Computer Science Technion March 12, 2003.
Introduction to Genomics, Bioinformatics & Proteomics Brian Rybarczyk, PhD PMABS Department of Biology University of North Carolina Chapel Hill.
The Human Genome Project and ~ 100 other genome projects:
Alternative Splicing As an introduction to microarrays.
Genetics: From Genes to Genomes
Introduce to Microarray
STAT115 STAT215 BIO512 BIST298 Introduction to Computational Biology and Bioinformatics Spring 2015 Xiaole Shirley Liu Please Fill Out Student Sign In.
DNA Microarrays Examining Gene Expression. Prof. GrossBiology 4 DNA MicroArrays DNA MicroArrays use hybridization technology to examine gene expression.
Why microarrays in a bioinformatics class? Design of chips Quantitation of signals Integration of the data Extraction of groups of genes with linked expression.
Proteomics Understanding Proteins in the Postgenomic Era.
By Moayed al Suleiman Suleiman al borican Ahmad al Ahmadi
Bioinformatics Ayesha M. Khan Spring Phylogenetic software PHYLIP l 2.
with an emphasis on DNA microarrays
Knowledgebase Creation & Systems Biology: A new prospect in discovery informatics S.Shriram, Siri Technologies (Cytogenomics), Bangalore S.Shriram, Siri.
Biotechnology SB2.f – Examine the use of DNA technology in forensics, medicine and agriculture.
What is Biotechnology?.
DNA MICROARRAYS WHAT ARE THEY? BEFORE WE ANSWER THAT FIRST TAKE 1 MIN TO WRITE DOWN WHAT YOU KNOW ABOUT GENE EXPRESSION THEN SHARE YOUR THOUGHTS IN GROUPS.
Chapter 13. The Impact of Genomics on Antimicrobial Drug Discovery and Toxicology CBBL - Young-sik Sohn-
Lesson Overview Lesson Overview Studying the Human Genome Lesson Overview 14.3 Studying the Human Genome.
Data Type 1: Microarrays
Microarray Technology
Literature reviews revised is due4/11 (Friday) turn in together: revised paper (with bibliography) and peer review and 1st draft.
 The process by which desired traits of certain plants and animals are selected and passed on to their future generations is called selective breeding.
Microarrays and Gene Expression Analysis. 2 Gene Expression Data Microarray experiments Applications Data analysis Gene Expression Databases.
What Is Microarray A new powerful technology for biological exploration Parallel High-throughput Large-scale Genomic scale.
Biological Signal Detection for Protein Function Prediction Investigators: Yang Dai Prime Grant Support: NSF Problem Statement and Motivation Technical.
High throughput Protein Measurement Techniques Harin Kanani.
Introduction to Bioinformatics Dr. Rybarczyk, PhD University of North Carolina-Chapel Hill
Bioinformatics MEDC601 Lecture by Brad Windle Ph# Office: Massey Cancer Center, Goodwin Labs Room 319 Web site for lecture:
Data Mining the Yeast Genome Expression and Sequence Data Alvis Brazma European Bioinformatics Institute.
Information Technology in the Natural Sciences Biology – Chemistry – Physics.
KEY CONCEPT Biotechnology relies on cutting DNA at specific places.
Histone Methyltransferases: Global Industry Report for Research Tools, Diagnostics and Drug Discovery
Bioinformatics and Computational Biology
Human Genomics. Writing in RED indicates the SQA outcomes. Writing in BLACK explains these outcomes in depth.
Gene expression & Clustering. Determining gene function Sequence comparison tells us if a gene is similar to another gene, e.g., in a new species –Dynamic.
Alternative Splicing (a review by Liliana Florea, 2005) CS 498 SS Saurabh Sinha 11/30/06.
Locating and sequencing genes
ANALYSIS OF GENE EXPRESSION DATA. Gene expression data is a high-throughput data type (like DNA and protein sequences) that requires bioinformatic pattern.
Disease Diagnosis by DNAC MEC seminar 25 May 04. DNA chip Blood Biopsy Sample rRNA/mRNA/ tRNA RNA RNA with cDNA Hybridization Mixture of cell-lines Reference.
Genomics A Systematic Study of the Locations, Functions and Interactions of Many Genes at Once.
Tutorial 8 Gene expression analysis 1. How to interpret an expression matrix Expression data DBs - GEO Clustering –Hierarchical clustering –K-means clustering.
DNA Microarray Overview and Application. Table of Contents Section One : Introduction Section Two : Microarray Technique Section Three : Types of DNA.
PLANT BIOTECHNOLOGY & GENETIC ENGINEERING (3 CREDIT HOURS) LECTURE 13 ANALYSIS OF THE TRANSCRIPTOME.
Example of a DNA array used to study gene expression (note green, yellow red colors; also note.
Genomics A Systematic Study of the Locations, Functions and Interactions of Many Genes at Once.
1 Ch 15 DNA Technology/ Genetic Engineering. Selective Breeding Selective Breeding – humans take advantage of naturally occurring genetic variation to.
Biotechnology and Bioinformatics: Bioinformatics Essential Idea: Bioinformatics is the use of computers to analyze sequence data in biological research.
13-1 OBJECTIVES IDENTIFY HOW SELECTIVE BREEDING IS USED COMPARE AND CONTRAST INBREEDING AND HYBRIDIZATION USE A PUNNETT SQUARE TO PERFORM A TEST CROSS.
Detecting DNA with DNA probes arrays. DNA sequences can be detected by DNA probes and arrays (= collection of microscopic DNA spots attached to a solid.
STAT115 STAT215 BIO512 BIST298 Introduction to Computational Biology and Bioinformatics Spring 2016 Xiaole Shirley Liu.
Show & Tell Limsoon Wong Kent Ridge Digital Labs Singapore Role of Bioinformatics in the Genomic Era.
Biotechnology.
Part 3 Gene Technology & Medicine
Ch 15 DNA Technology/ Genetic Engineering
Genomics A Systematic Study of the Locations, Functions and Interactions of Many Genes at Once.
Gene expression.
Bioinformatics Madina Bazarova. What is Bioinformatics? Bioinformatics is marriage between biology and computer. It is the use of computers for the acquisition,
Microarray Technology and Applications
Chapter 14 Bioinformatics—the study of a genome
14-3 Human Molecular Genetics
KEY CONCEPT Entire genomes are sequenced, studied, and compared.
Bio-Rad Overview and Statement of Interests
Data Type 1: Microarrays
Presentation transcript:

A New Oklahoma Bioinformatics Company

Microarray and Bioinformatics

Bioinformatics Programs Graphics Database Management & Sequence Data Statistical Analysis Ease of Use

Bioinformatics Programs

The Technology Core technology was developed at the University of Oklahoma. Scientists from microbiology, biochemistry, computer science, molecular biology, mathematics, and bio-informatics took part in the development. Development took over two years of work and experimentation.

Company Structure Microarray Data Management, LLC is a joint venture between the company and the University of Oklahoma. The company is the first Bioinformatics joint venture enterered into by the University of Oklahoma. The company has an exclusive license from the University of Oklahoma for commercial development of the technology.

Technology The core technology is a stand alone software program bringing together all elements necessary to manage, evaluate, calculate, and graphically represent data from microarray data sets The technology is highly intitutive, and allows for seamless real time interaction with microarray experimental data and existing data bases.

Technology (continued) No other existing Bioinformatics software offers the power of the technology in a stand alone package. The technology uses a unique set of mathematical and computer algorithms to enable processing, data management, and visualation power. Initial patents have been filed.

Technology Applications Microarrays are Viewed to the future of medical diagnostics and biopharmaceutical therapeutic intervention Microarrays are cutting edge technology, evolving with the expansion of genetic research. Biotechnology companies, can significantly reduce research time leading to drug discovery using microarrays and the companies software saving potentially millions of dollars in costs. Microarrays are the only technology that can be used to study genes and gene fragments and their interaction with other genes and other substances. Microarrays can evaluate up to 50,000 genes or gene sequences one time

Technology Applications (cont) Genomics Proteonomics Pharmacogenomics Bioinformatics Oncogenomics Plant Genomics Medical Diagnostic Genomics Medical Therapeutic Genomics and Proteonomics

Unique Properties of the Technology Creation and maintenance of custom data bases based on individual gene responses, generated by microarrays. Analysis of sequence information by gene response. Very important in cancer chemotherapy. Currently not available. Expression Analysis using data mining and statistical approaches to understand gene function and expression patterns.

The Market for the Technology The current market in 2004 for microarray technologies is estimated to exceed 1 billion dollars. The market for microarray bioinformatics (a subset of the microarray total market) in 2004 is estimated at about 50 million dollars. The bioinformatics market is expected to grow to exceed 500 million dollars as the microarray market expands to 5 billion dollars in 2010.

The Market (continued) Dramatic market expansion of cancer therapeutic Micro- arrays to measure and evaluate effectiveness of chemotherapy. Integration of microarrays into genomic diagnostics Significant utilization of microarray technologies in diabetes, Alzheimer's, cardiovascular, stroke, AIDS, Parkinsonism, autism, and anemia Drug Discovery; Bio-pharmaceutical companies will utilize microarrays to discover novel genes and the proteins that are produced and control their expression or repression.

Tactical Strategy Continue to pursue additional patents, layering onto the core technology Begin beta site testing of technology for oncogenomic, proteonomic, and pharmacogenomic applications Begin commercial discussions with software, data base management, and hardware companies engaged in selling high end scientific servers; microarrays are a very data intensive technology, and require a large amount of computing power.

Summary Our technology is novel and fills an existing void in Bioinformatics software. It is a totally integrated package designed to meet the needs for Microarray data management. The microarray market is a very large and important technology. Most genetic research will utilize microarrays and will need Bioinformatics software. Our technology is enabling and will allow for the rapid expansion of microarray utilization. Our technology will be an important aspect of developing treatments and diagnostics for cancer and other serious and prevalent diseases.

Definitions Microarray– An array of DNA or protein samples that can be hybridized with probes to study patterns of gene expression. Bioinformatics– The study of the basic structure of biological information and biological systems. It brings together biological data handling with the analytic theory and practical tools of mathematics and computer science.

Microarray Process A typical DNA micro array experiment is as follows: Take a small slide. Divide the slide into a series of square cells to form a rectangular grid. Onto each square cell, stick a tiny amount of liquid that contains DNA corresponding to a gene of known sequence. Different cells will have different genes. Separately prepare a solution that contains a mixture of mRNAs whose sequences are unknown. Add solution a substance that fluoresces when excited by light. Pour the solution onto slide. The mRNA molecules will diffuse over the slide and, wherever they find a matching (i.e. complementary) DNA sequence, such as the one taken from the gene from which the mRNA was transcribed, they will hybridize to each other and the solution will stick to the slide. Without a match the solution will not stick to the slide and can be washed away. Use a laser scanner to detect and measure the florescent signal being emitted at each cell. In a comparative micro array experiment, different slides containing the same set of genes will be exposed to different mRNA samples. By comparing the intensity levels of the florescent signals across the multiple mRNA samples, a scientist will be able to understand how the expression profile of a set of genes differs across the different mRNA samples.