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en-us LUSNI3MNI Genomics Genomics /webroot/web/html/lsr/solutions/applications/genomics /webroot/web/images/lsr/solutions/applications/gene_expression/genomics/application_detail/solutions_feature_gxa1_genomics.jpg /webroot/web/images/lsr/solutions/applications/gene_expression/genomics/application_thumb/cat_gxa1_genomics_icon.jpg <script type="text/javascript">// <![CDATA[ if ($.browser.msie && $.browser.version < 8) { $("div.methodboxmiddle ul.rightarrowsearch1").css({"margin-left":"-5px"});} // ]]></script> <p>Genomics is an area of molecular biology and genetics that focuses on the structure, function, evolution and mapping of genomes. This field encompasses a wide range of research fields including genome sequencing, functional genomics, comparative genomics, bioinformatics, epigenomics, and gene regulation analysis. It also includes studies related to disease pathogenesis and personal genomics. A few popular areas of genomics research are highlighted below.</p> Functional Genomics <p>Functional genomics encompasses the research field describing the function and interaction of both proteins and genes. This area of study is a genome-wide approach that builds on our understanding of DNA structure and sequence to focus on the dynamic aspects of interactions, including gene transcription, translation, and protein-protein interactions.</p> <p>The importance of functional genomics has increased following the completion of the human genome project. Genomics is now being used to understand the function of the ~30,000 human genes, non-coding regions, and sequence variations, including single nucleotide polymorphisms (SNPs). Understanding functional genomics, that is, how the genome and proteome interact to generate an organism's phenotype, provides insights into complex biological processes including human disease.</p> <p>Since functional genomics includes investigation at both the genome and proteome level, a wide variety of technologies are utilized. Techniques that allow the measurement of multiple genes or proteins simultaneously, including multiplex and high-throughput screening approaches, are commonly used.</p> <p>Common experimental approaches for functional genomics and their enabling technologies include:</p> <ul> <li><a href="/evportal/destination/solutions?catID=LUSR3BMNI">Transfection</a></li> <li><a href="/evportal/destination/solutions?catID=LUSO4W8UU">Real-time PCR</a></li> <li>RNA interference</li> <li><a href="/evportal/destination/solutions?catID=LUSNLMLPT">Mutational analysis</a></li> <li>SNP analysis</li> <li>Microarray analysis</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> Epigenetics <p><a href="/evportal/destination/solutions?catID=LUSNMFHYP">Epigenetics</a> is defined as the study of inherited changes in phenotype or gene expression caused by mechanisms other than mutations in the underlying DNA sequence. Epigenetic markers include DNA methylation and modification of histone tails.</p> <p>In eukaryotes, DNA can be modified by methylation of cytosine bases, while in prokaryotes DNA methylation occurs primarily on adenosine bases. Aberrant or increased methylation has been correlated with gene silencing and the development of several cancers.</p> <p>Histones are subject to several different covalent modifications, including methylation, acetylation, phosphorylation, ubiquitylation, and sumoylation. Acetylation is the most commonly studied of these modifications and a strong correlation between histone acetylation and active transcription has been established. Conversely, many histone methylation events are correlated with transcriptional silencing. Different histone modifications likely function in differing ways. For example, acetylation at one position may have a different effect than acetylation at another position.</p> <p>Multiple modifications can exist simultaneously and are likely working together to influence chromatin state and gene expression. The concept of multiple dynamic modifications regulating gene expression in a systematic and reproducible fashion is known as the histone code.</p> <p>Common techniques used to study DNA methylation and histone modifications include:</p> <ul> <li><a href="/evportal/destination/solutions?catID=LUSNNRCZF#methods_used">Bisulfite sequencing</a></li> <li>Chromatin immunoprecipitation (ChIP)</li> <li>Chromatin immunoprecipitation-sequencing (ChIP-Seq)</li> <li>Methylated DNA immunoprecipitation (MeDIP)</li> <li><a href="/evportal/destination/solutions?catID=LUSOIH97Q">High resolution melt (HRM)</a></li> <li><a href="/evportal/destination/solutions?catID=LUSNNRCZF#chromatin">Chromatin accessibility assays</a></li> <li>Microarray analysis</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> Pathway Analysis <p>Biological pathways include metabolic, regulatory, and signaling pathways that organize and coordinate the activities of a cell. Biological pathways often interact with one another to form biological networks.</p> <p>Pathway analysis is used in systems biology to build a better picture of how the individual components of a biological system interact to create the larger functional system.</p> <p>Techniques that enable screening for expression of multiple gene or gene products simultaneously are typically used to generate data for pathway analysis. The data are then analyzed using complex software algorithms or biostatistics to create a map of how these individual components interact with one another in an interaction pathway. As deregulation of a pathway can result in disease, such as cancer, pathway analysis often involves comparisons of expression patterns between normal and pathological samples.</p> <p>Although an understanding of biological pathways can be built up slowly by adding information generated from individual experiments, typically large data sets, often combined from a variety of sources including the published literature, are mined using automated network generating software tools. While almost any biological analysis tool can be used to generate data for pathway analysis, techniques that enable the comparison of multiple gene or gene products are most useful, and include:</p> <ul> <li>Luminex bead-based analysis (<a href="/evportal/destination/solutions?catID=LUSM0E8UU">Bio-Plex</a>)</li> <li>Microarray analysis</li> <li><a href="/evportal/destination/solutions?catID=LUSO4W8UU">Real-time PCR</a></li> <li>Proteomics tools (<a href="/evportal/destination/solutions?catID=LUSQF04EH">2-D PAGE</a>; yeast 2-hybrid studies)</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> Biomarker Discovery <p>The <a href="http://www.nih.gov/" target="_blank" rel="noopener noreferrer">National Institutes of Health (NIH)</a> defines a biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The goal of biomarker research is to discover gene or protein markers and use them to improve diagnostic, prognostic, or therapeutic outcomes for patients, and to assist in the development of novel drug candidates.</p> <p>Biomarkers can be discovered through differential expression analysis, which is the indentification of mRNA, microRNA, or protein expression levels as influenced by disease state, therapy, or other differences between sample cohorts. Once differentially expressed targets are identified and validated, their expression levels can be used to classify organisms, individuals, disease states, metabolic conditions, or phenotypic responses to environmental or chemical challenges.</p> <p>Common experimental approaches for biomarker discovery include:</p> <ul> <li>Mass spectrometry</li> <li><a href="/evportal/destination/solutions?catID=LUSO4W8UU">Real-time PCR</a></li> <li>Microarray analysis</li> <li>Statistical analysis</li> <li>Bioinformatics</li> <li>DNA sequencing</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> 5990 6090 Amplification Reagents and Plastics Brochure 6090 H /webroot/web/pdf/lsr/literature/Bulletin_6090.pdf Literature PDF Brochures_and_Specifications /webroot/web/images/general/icons/icon_pdf.gif Amplification Reagents and Plastics Brochure No Amplification Reagents and Plastics Brochure, Rev E 6090 6090, amplification, cDNA, chromatin, DNase, epigenetics, EpiQ, EvaGreen, genotyping, Hard-Shell, high resolution melt analysis, HRM, melt curve, methylation detection, PCR plates, PCR tubes, plastic consumables, qPCR, quantification, quantitative PCR, real-time PCR probes, reverse transcription, RNA isolation, SsoAdvanced, SsoFast, supermix, SYBR Green, RT-qPCR, real-time PCR 5642 Biomarker Discovery Using SELDI Technology Guide, Rev A 5642 /webroot/web/pdf/lsr/literature/Bulletin_5642.pdf Literature PDF Manuals_and_Quick_Guides /webroot/web/images/general/icons/icon_pdf.gif No Biomarker Discovery Using SELDI Technology Guide, Rev A 5642 3145, 10008226, proteomics, biomarkers, desorption, protein chip array, proteominer, enrichment, matrix application, arrays, ionization, proteinchip system applications, proteome, laser desorption/ionization, 10008221, proteo miner, 10008220, 10008222, ionisation, LIT5642 5814 Biomarker Discovery Using SELDI Technology, A Guide to Data Processing and Analysis Using ProteinChip Data Manager Software, Rev A 5814 /webroot/web/pdf/lsr/literature/Bulletin_5814.pdf Literature PDF Manuals_and_Quick_Guides /webroot/web/images/general/icons/icon_pdf.gif No Biomarker Discovery Using SELDI Technology, A Guide to Data Processing and Analysis Using ProteinChip Data Manager Software, Rev A 5814 processing conditions, spectral alignment, peak clusters, sensitivity, algorithm, mass calibration, signal-to-noise ratio, specificity, LIT5814, precision, ROC curves, workflow, accuracy, classification algorithms, standards, PCA, spectra 5859 A Practical Approach to RT-qPCR &mdash;&nbsp;Publishing Data That Conform to the MIQE Guidelines, Ver E 5859 /webroot/web/pdf/lsr/literature/Bulletin_5859.pdf Literature PDF Manuals_and_Quick_Guides /webroot/web/images/icon_pdf.gif A Practical Approach to RT-qPCR &mdash;&nbsp;Publishing Data That Conform to the MIQE Guidelines No A Practical Approach to RT-qPCR &mdash;&nbsp;Publishing Data That Conform to the MIQE Guidelines 5859 5859, realtime quantitative pcr, real time, guide, sample management, rna extraction, quality control, experion automated electrophoresis system, purity and integrity, reverse transcription, primer and amplicon design, validation, melt curve analysis, annealing temperature, efficiency, reference genes, cfx manager, replicates, 7007000, 7007001, 7007002, 7007060, 7007061, 7007062, 7007063, 7007064, 7007103, 7007104, 7007105, 7007106 5279 Real-Time PCR Applications Guide, Rev B 5279 /webroot/web/pdf/lsr/literature/Bulletin_5279.pdf Literature PDF Manuals_and_Quick_Guides /webroot/web/images/general/icons/icon_pdf.gif Real-Time PCR Applications Guide, Rev B No Real-Time PCR Applications Guide, Rev B 5279 real-time, pcr, real-time pcr, quantitative, qpcr, rt-pcr, applications, guide, 170-9799, 170-9799EDU, 804-1, 1709799, 1709799EDU, 8041 6004 A Practical Guide to High Resolution Melt Analysis Genotyping, Rev A 6004 /webroot/web/pdf/lsr/literature/Bulletin_6004.pdf Literature PDF Manuals_and_Quick_Guides /webroot/web/images/general/icons/icon_pdf.gif No A Practical Guide to High Resolution Melt Analysis Genotyping, Rev A 6004 6004, amplicon, CFX96 real-time PCR detection system, CFX384, DNA melt curve profiles, genetic variation, genome sequencing, high-throughput, high throughput, HRM, polymerase chain reaction, Precision Melt Analysis software, primer design, quantitative PCR, qPCR, SNP profiling, 185-5096, 1855096, 185-5384, 1855384, 184-5025, 1845025 6712 /templatedata/internet/documentation/data/LSR/Literature/6712_1445968512.xml Ultra-Sensitive Quantification of Genome Editing Events Using Droplet Digital™ PCR Application Note, Ver B 6712 /webroot/web/pdf/lsr/literature/Bulletin_6712.pdf Literature PDF Application_Notes /webroot/web/images/general/icons/icon_pdf.gif Ultra-Sensitive Quantification of Genome Editing Events Using Droplet Digital PCR Application Note, Ver B No Ultra-Sensitive Quantification of Genome Editing Events Using Droplet Digital™ PCR 6712 6712, droplet digital pcr, ddpcr, autodg, qx200, qx100, genome editing, talen, crispr/cas9, genome editing quantification, genome editing efficiency, genome editing validation, genome editing frequency, nhej genome editing, hdr genome editing, non-homologous end joining, homology-directed repair, qx200 droplet generator, ddpcr supermix for probes (no dutp), 1864001, 1864002, 1864003, 1863023, 1863024, 1863025 Life Science Research/Products/Amplification - PCR/Real-Time PCR Detection Systems/CFX96 Touch Real-Time PCR Detection System ->MTS::LJB1YU15##Life Science Research/Products/Amplification - PCR/Real-Time PCR Detection Systems/CFX384 Touch Real-Time PCR Detection System ->MTS::LJB22YE8Z##Life Science Research/Products/Amplification - PCR/PCR Reagents/EpiQ Chromatin Analysis Kit ->MTS::L7RZLK15##Life Science Research/Products/Amplification - PCR/PCR Reagents/Supermixes for PCR and Real-Time PCR/SsoAdvanced SYBR Green Supermix ->MTS::LML5JY15##Life Science Research/Products/Amplification - PCR/PCR Reagents/Reverse Transcription Reagents/iScript Advanced cDNA Synthesis Kit ->MTS::LIXR5J15##Life Science Research/Products/Amplification - PCR/Droplet Digital PCR System ->MTS::LSZ42515## Life Science Research/Solutions/Technologies/PCR ->MTS::LUSNYI15##Life Science Research/Solutions/Technologies/Protein Electrophoresis/Protein Sample Preparation/Sample Quantitation -Protein Assays- ->MTS::LUSP5JKAJ##Life Science Research/Solutions/Technologies/Protein Electrophoresis ->MTS::LUSOVO47B##Life Science Research/Solutions/Technologies/Multiplex Immunoassays ->MTS::LUSM0E8UU##Life Science Research/Solutions/Applications/Protein Interaction Analysis ->MTS::LUSLTJE8Z## TW Genomics <p>Explore different aspects of genomics &mdash; from functional genomics and biomarker discovery to mutation analysis, gene expression, transfection, and epigenetics.</p> 11/18/11 03:41 PM 12/20/21 11:07 AM AE,AI,AL,AM,AR,AT,AU,AZ,BA,BD,BE,BF,BG,BH,BN,BO,BR,BW,CA,CH,CL,CM,CN,CO,CR,CY,CZ,DE,DK,DO,DZ,EC,EE,EG,EH,ER,ES,ET,FI,FM,FO,FR,GA,GE,GF,GH,GP,GR,GT,GU,HK,HN,HR,HT,HU,ID,IE,IL,IN,IS,IT,JM,JO,JP,KE,KH,KR,KW,KZ,LB,LI,LK,LT,LU,LV,MA,MD,MG,MK,ML,MO,MQ,MS,MT,MU,MX,MY,NG,NI,NL,NO,NP,NZ,OM,PA,PE,PF,PG,PH,PK,PL,PR,PS,PT,PW,PY,QA,RO,RS,RU,SA,SB,SE,SG,SI,SK,SN,ST,SV,TG,TH,TN,TO,TR,TT,TW,TZ,UA,UG,UK,US,UY,UZ,VA,VE,VU,XK,YE,ZA en LSR /LSR/Applications/Genomics N 0 What is Gene Expression Analysis? /en-us/applications-technologies/applications-technologies/what-gene-expression-analysis?ID=LUSNINKSY Introduction to Gene Cloning and Analysis /en-us/applications-technologies/applications-technologies/introduction-gene-cloning-analysis?ID=LUSNKO4EH Mutational Analysis /en-us/applications-technologies/applications-technologies/mutational-analysis?ID=LUSNLMLPT Epigenetics and Chromatin Structure /en-us/applications-technologies/applications-technologies/epigenetics-chromatin-structure?ID=LUSNMFHYP Introduction to Nucleic Acid Analysis /en-us/applications-technologies/applications-technologies/introduction-nucleic-acid-analysis?ID=LUSNPJ7OP Applications /en-us/applications-technologies/applications-technologies/genomics?ID=LO8ESC15

Genomics is an area of molecular biology and genetics that focuses on the structure, function, evolution and mapping of genomes. This field encompasses a wide range of research fields including genome sequencing, functional genomics, comparative genomics, bioinformatics, epigenomics, and gene regulation analysis. It also includes studies related to disease pathogenesis and personal genomics. A few popular areas of genomics research are highlighted below.

 

Functional Genomics

Functional genomics encompasses the research field describing the function and interaction of both proteins and genes. This area of study is a genome-wide approach that builds on our understanding of DNA structure and sequence to focus on the dynamic aspects of interactions, including gene transcription, translation, and protein-protein interactions.

The importance of functional genomics has increased following the completion of the human genome project. Genomics is now being used to understand the function of the ~30,000 human genes, non-coding regions, and sequence variations, including single nucleotide polymorphisms (SNPs). Understanding functional genomics, that is, how the genome and proteome interact to generate an organism's phenotype, provides insights into complex biological processes including human disease.

Since functional genomics includes investigation at both the genome and proteome level, a wide variety of technologies are utilized. Techniques that allow the measurement of multiple genes or proteins simultaneously, including multiplex and high-throughput screening approaches, are commonly used.

Common experimental approaches for functional genomics and their enabling technologies include:

 

Epigenetics

Epigenetics is defined as the study of inherited changes in phenotype or gene expression caused by mechanisms other than mutations in the underlying DNA sequence. Epigenetic markers include DNA methylation and modification of histone tails.

In eukaryotes, DNA can be modified by methylation of cytosine bases, while in prokaryotes DNA methylation occurs primarily on adenosine bases. Aberrant or increased methylation has been correlated with gene silencing and the development of several cancers.

Histones are subject to several different covalent modifications, including methylation, acetylation, phosphorylation, ubiquitylation, and sumoylation. Acetylation is the most commonly studied of these modifications and a strong correlation between histone acetylation and active transcription has been established. Conversely, many histone methylation events are correlated with transcriptional silencing. Different histone modifications likely function in differing ways. For example, acetylation at one position may have a different effect than acetylation at another position.

Multiple modifications can exist simultaneously and are likely working together to influence chromatin state and gene expression. The concept of multiple dynamic modifications regulating gene expression in a systematic and reproducible fashion is known as the histone code.

Common techniques used to study DNA methylation and histone modifications include:

 

Pathway Analysis

Biological pathways include metabolic, regulatory, and signaling pathways that organize and coordinate the activities of a cell. Biological pathways often interact with one another to form biological networks.

Pathway analysis is used in systems biology to build a better picture of how the individual components of a biological system interact to create the larger functional system.

Techniques that enable screening for expression of multiple gene or gene products simultaneously are typically used to generate data for pathway analysis. The data are then analyzed using complex software algorithms or biostatistics to create a map of how these individual components interact with one another in an interaction pathway. As deregulation of a pathway can result in disease, such as cancer, pathway analysis often involves comparisons of expression patterns between normal and pathological samples.

Although an understanding of biological pathways can be built up slowly by adding information generated from individual experiments, typically large data sets, often combined from a variety of sources including the published literature, are mined using automated network generating software tools. While almost any biological analysis tool can be used to generate data for pathway analysis, techniques that enable the comparison of multiple gene or gene products are most useful, and include:

 

Biomarker Discovery

The National Institutes of Health (NIH) defines a biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The goal of biomarker research is to discover gene or protein markers and use them to improve diagnostic, prognostic, or therapeutic outcomes for patients, and to assist in the development of novel drug candidates.

Biomarkers can be discovered through differential expression analysis, which is the indentification of mRNA, microRNA, or protein expression levels as influenced by disease state, therapy, or other differences between sample cohorts. Once differentially expressed targets are identified and validated, their expression levels can be used to classify organisms, individuals, disease states, metabolic conditions, or phenotypic responses to environmental or chemical challenges.

Common experimental approaches for biomarker discovery include:

  • Mass spectrometry
  • Real-time PCR
  • Microarray analysis
  • Statistical analysis
  • Bioinformatics
  • DNA sequencing
 

Related Content

 
Literature
Number Description Download
6090 Amplification Reagents and Plastics Brochure Click to download
5642 Biomarker Discovery Using SELDI Technology Guide, Rev A Click to download
5814 Biomarker Discovery Using SELDI Technology, A Guide to Data Processing and Analysis Using ProteinChip Data Manager Software, Rev A Click to download
5859 A Practical Approach to RT-qPCR &mdash;&nbsp;Publishing Data That Conform to the MIQE Guidelines, Ver E Click to download
5279 Real-Time PCR Applications Guide, Rev B Click to download
6004 A Practical Guide to High Resolution Melt Analysis Genotyping, Rev A Click to download
6712 Ultra-Sensitive Quantification of Genome Editing Events Using Droplet Digital™ PCR Application Note, Ver B Click to download
 
 
LUSNI3MNI [referer] = [http://www.bio-rad.com/en-us/applications-technologies/introduction-transfection?ID=LUSNI3MNI] [x-forwarded-proto] = [http] [cookie] = [] [accept-language] = [zh-CN] [x-forwarded-port] = [80] [x-forwarded-for] = [42.236.10.122, 10.232.2.216] [accept] = [*/*] [seourl] = [/en-us/applications-technologies/introduction-transfection] [x-amzn-trace-id] = [Root=1-5bc843df-9be86ec03eb4a606276e91ec] [x-forwarded-server] = [lsds-prod-s.br.aws-livesite.io] [x-forwarded-host] = [www.bio-rad.com] [x-query-string] = [ID=LUSNI3MNI] [host] = [10.232.1.21:1776] [x-request-uri] = [/en-us/applications-technologies/introduction-transfection] [connection] = [Keep-Alive] [accept-encoding] = [deflate, gzip] [user-agent] = [Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36; 360Spider] AppTech/AppTechDetails pageStyleKey internet/solutions_sub applications-technologies/introduction-transfection LSR LUSNI3MNI Genomics Genomics /webroot/web/html/lsr/solutions/applications/genomics /webroot/web/images/lsr/solutions/applications/gene_expression/genomics/application_detail/solutions_feature_gxa1_genomics.jpg /webroot/web/images/lsr/solutions/applications/gene_expression/genomics/application_thumb/cat_gxa1_genomics_icon.jpg <script type="text/javascript">// <![CDATA[ if ($.browser.msie && $.browser.version < 8) { $("div.methodboxmiddle ul.rightarrowsearch1").css({"margin-left":"-5px"});} // ]]></script> <p>Genomics is an area of molecular biology and genetics that focuses on the structure, function, evolution and mapping of genomes. This field encompasses a wide range of research fields including genome sequencing, functional genomics, comparative genomics, bioinformatics, epigenomics, and gene regulation analysis. It also includes studies related to disease pathogenesis and personal genomics. A few popular areas of genomics research are highlighted below.</p> Functional Genomics <p>Functional genomics encompasses the research field describing the function and interaction of both proteins and genes. This area of study is a genome-wide approach that builds on our understanding of DNA structure and sequence to focus on the dynamic aspects of interactions, including gene transcription, translation, and protein-protein interactions.</p> <p>The importance of functional genomics has increased following the completion of the human genome project. Genomics is now being used to understand the function of the ~30,000 human genes, non-coding regions, and sequence variations, including single nucleotide polymorphisms (SNPs). Understanding functional genomics, that is, how the genome and proteome interact to generate an organism's phenotype, provides insights into complex biological processes including human disease.</p> <p>Since functional genomics includes investigation at both the genome and proteome level, a wide variety of technologies are utilized. Techniques that allow the measurement of multiple genes or proteins simultaneously, including multiplex and high-throughput screening approaches, are commonly used.</p> <p>Common experimental approaches for functional genomics and their enabling technologies include:</p> <ul> <li><a href="/evportal/destination/solutions?catID=LUSR3BMNI">Transfection</a></li> <li><a href="/evportal/destination/solutions?catID=LUSO4W8UU">Real-time PCR</a></li> <li>RNA interference</li> <li><a href="/evportal/destination/solutions?catID=LUSNLMLPT">Mutational analysis</a></li> <li>SNP analysis</li> <li>Microarray analysis</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> Epigenetics <p><a href="/evportal/destination/solutions?catID=LUSNMFHYP">Epigenetics</a> is defined as the study of inherited changes in phenotype or gene expression caused by mechanisms other than mutations in the underlying DNA sequence. Epigenetic markers include DNA methylation and modification of histone tails.</p> <p>In eukaryotes, DNA can be modified by methylation of cytosine bases, while in prokaryotes DNA methylation occurs primarily on adenosine bases. Aberrant or increased methylation has been correlated with gene silencing and the development of several cancers.</p> <p>Histones are subject to several different covalent modifications, including methylation, acetylation, phosphorylation, ubiquitylation, and sumoylation. Acetylation is the most commonly studied of these modifications and a strong correlation between histone acetylation and active transcription has been established. Conversely, many histone methylation events are correlated with transcriptional silencing. Different histone modifications likely function in differing ways. For example, acetylation at one position may have a different effect than acetylation at another position.</p> <p>Multiple modifications can exist simultaneously and are likely working together to influence chromatin state and gene expression. The concept of multiple dynamic modifications regulating gene expression in a systematic and reproducible fashion is known as the histone code.</p> <p>Common techniques used to study DNA methylation and histone modifications include:</p> <ul> <li><a href="/evportal/destination/solutions?catID=LUSNNRCZF#methods_used">Bisulfite sequencing</a></li> <li>Chromatin immunoprecipitation (ChIP)</li> <li>Chromatin immunoprecipitation-sequencing (ChIP-Seq)</li> <li>Methylated DNA immunoprecipitation (MeDIP)</li> <li><a href="/evportal/destination/solutions?catID=LUSOIH97Q">High resolution melt (HRM)</a></li> <li><a href="/evportal/destination/solutions?catID=LUSNNRCZF#chromatin">Chromatin accessibility assays</a></li> <li>Microarray analysis</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> Pathway Analysis <p>Biological pathways include metabolic, regulatory, and signaling pathways that organize and coordinate the activities of a cell. Biological pathways often interact with one another to form biological networks.</p> <p>Pathway analysis is used in systems biology to build a better picture of how the individual components of a biological system interact to create the larger functional system.</p> <p>Techniques that enable screening for expression of multiple gene or gene products simultaneously are typically used to generate data for pathway analysis. The data are then analyzed using complex software algorithms or biostatistics to create a map of how these individual components interact with one another in an interaction pathway. As deregulation of a pathway can result in disease, such as cancer, pathway analysis often involves comparisons of expression patterns between normal and pathological samples.</p> <p>Although an understanding of biological pathways can be built up slowly by adding information generated from individual experiments, typically large data sets, often combined from a variety of sources including the published literature, are mined using automated network generating software tools. While almost any biological analysis tool can be used to generate data for pathway analysis, techniques that enable the comparison of multiple gene or gene products are most useful, and include:</p> <ul> <li>Luminex bead-based analysis (<a href="/evportal/destination/solutions?catID=LUSM0E8UU">Bio-Plex</a>)</li> <li>Microarray analysis</li> <li><a href="/evportal/destination/solutions?catID=LUSO4W8UU">Real-time PCR</a></li> <li>Proteomics tools (<a href="/evportal/destination/solutions?catID=LUSQF04EH">2-D PAGE</a>; yeast 2-hybrid studies)</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> Biomarker Discovery <p>The <a href="http://www.nih.gov/" target="_blank" rel="noopener noreferrer">National Institutes of Health (NIH)</a> defines a biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The goal of biomarker research is to discover gene or protein markers and use them to improve diagnostic, prognostic, or therapeutic outcomes for patients, and to assist in the development of novel drug candidates.</p> <p>Biomarkers can be discovered through differential expression analysis, which is the indentification of mRNA, microRNA, or protein expression levels as influenced by disease state, therapy, or other differences between sample cohorts. Once differentially expressed targets are identified and validated, their expression levels can be used to classify organisms, individuals, disease states, metabolic conditions, or phenotypic responses to environmental or chemical challenges.</p> <p>Common experimental approaches for biomarker discovery include:</p> <ul> <li>Mass spectrometry</li> <li><a href="/evportal/destination/solutions?catID=LUSO4W8UU">Real-time PCR</a></li> <li>Microarray analysis</li> <li>Statistical analysis</li> <li>Bioinformatics</li> <li>DNA sequencing</li> </ul> <div class="top"><a href="#helptop">Back to Top</a></div> 5990 6090 5642 5814 5859 5279 6004 6712 /templatedata/internet/documentation/data/LSR/Literature/6712_1445968512.xml Life Science Research/Products/Amplification - PCR/Real-Time PCR Detection Systems/CFX96 Touch Real-Time PCR Detection System ->MTS::LJB1YU15##Life Science Research/Products/Amplification - PCR/Real-Time PCR Detection Systems/CFX384 Touch Real-Time PCR Detection System ->MTS::LJB22YE8Z##Life Science Research/Products/Amplification - PCR/PCR Reagents/EpiQ Chromatin Analysis Kit ->MTS::L7RZLK15##Life Science Research/Products/Amplification - PCR/PCR Reagents/Supermixes for PCR and Real-Time PCR/SsoAdvanced SYBR Green Supermix ->MTS::LML5JY15##Life Science Research/Products/Amplification - PCR/PCR Reagents/Reverse Transcription Reagents/iScript Advanced cDNA Synthesis Kit ->MTS::LIXR5J15##Life Science Research/Products/Amplification - PCR/Droplet Digital PCR System ->MTS::LSZ42515## Life Science Research/Solutions/Technologies/PCR ->MTS::LUSNYI15##Life Science Research/Solutions/Technologies/Protein Electrophoresis/Protein Sample Preparation/Sample Quantitation -Protein Assays- ->MTS::LUSP5JKAJ##Life Science Research/Solutions/Technologies/Protein Electrophoresis ->MTS::LUSOVO47B##Life Science Research/Solutions/Technologies/Multiplex Immunoassays ->MTS::LUSM0E8UU##Life Science Research/Solutions/Applications/Protein Interaction Analysis ->MTS::LUSLTJE8Z## TW Genomics <p>Explore different aspects of genomics &mdash; from functional genomics and biomarker discovery to mutation analysis, gene expression, transfection, and epigenetics.</p> 11/18/11 03:41 PM 12/20/21 11:07 AM AE,AI,AL,AM,AR,AT,AU,AZ,BA,BD,BE,BF,BG,BH,BN,BO,BR,BW,CA,CH,CL,CM,CN,CO,CR,CY,CZ,DE,DK,DO,DZ,EC,EE,EG,EH,ER,ES,ET,FI,FM,FO,FR,GA,GE,GF,GH,GP,GR,GT,GU,HK,HN,HR,HT,HU,ID,IE,IL,IN,IS,IT,JM,JO,JP,KE,KH,KR,KW,KZ,LB,LI,LK,LT,LU,LV,MA,MD,MG,MK,ML,MO,MQ,MS,MT,MU,MX,MY,NG,NI,NL,NO,NP,NZ,OM,PA,PE,PF,PG,PH,PK,PL,PR,PS,PT,PW,PY,QA,RO,RS,RU,SA,SB,SE,SG,SI,SK,SN,ST,SV,TG,TH,TN,TO,TR,TT,TW,TZ,UA,UG,UK,US,UY,UZ,VA,VE,VU,XK,YE,ZA en LSR /LSR/Applications/Genomics N 0
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