《基因学研究分析工具包》(Genesis)v1.7.6.30.09.10/x86+x64/含注册码[压缩包]
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电驴资源
| 用户共享的电驴资源列表 | |
|---|---|
| [基因学研究分析工具包].Genesis_v1.7.6.30.09.10-DIGERATI.zip | 44.26 MB |
| [基因学研究分析工具包].Genesis_v1.7.6.30.09.10_x64-DIGERATI.zip | 44.34 MB |
| 88.60 MB | |
电驴资源简介
简介:
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引用 1. Unpack and install the software
2. Use the following information in serial.txt to register 软件类型：软件 行业软件
软件性质：破解软件
操作系统：Windows
应用平台：Windows
问题反馈： http://genome.tugraz.at/contact.shtml
网站链接： http://genome.tugraz.at/
软件介绍：
Genesis是一款用于基因学方面研究的工具包。
Genesis主要特点如下：
使用灵活，带有多种分析工具，视觉化的数据展示，附带平台独立的Java工具包，可以同时分析并展现一整套基因表达试验。
通过读取普通文件中的数据，Genesis能够生成图形化的分析数据，从而能方便的对多个试验的基因数据进行比较。
GENERAL DESCRIPTION
High throughput gene expression analysis is becoming more and more
important in many areas of biomedical research. cDNA microarray
technology is one very promising approach for high throughput
analysis and gives the opportunity to study gene expression patterns
on a genomic scale. Thousands or even tens of thousands of genes can
be spotted on a microscope slide and relative expression levels of
each gene can be determined by measuring the fluorescence intensity
of labeled mRNA hybridized to the arrays. Hence, microarrays can be
used to identify differentially expressed genes in two samples on a
large scale. Beyond simple discrimination of differentially
expressed genes, functional annotation (guilt-by-association) or
diagnostic classification requires the clustering of genes from
multiple experiments into groups with similar expression patterns.
Several clustering techniques were recently developed and applied to
analyze microarray data.
代码 °
° ²
²² ° ² ° °
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²² ²² ² ²²² ²²²²² ²² ²²²
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° ° ° ²² °
² ²² ִִִִִִִִִִִִִִִִִִִִִִִִִִִִִִ¿
² ° ²²° ²² ³Don't sweat petty ³ ° ²
²² ²² ²² ³things......or pet sweaty ³ ²²
²² ²² ³things. ³ ²²
²² ְִִִִִִִִִִִִִִִִִִִִִִִִִִִִִִ ²²
²° °²
²° °²
° ²² ²² °
² ²² ²² ²
² ² ° ° ² ²
²² The diGERATi Present ²²
Genesis_v1.7.6.30.09.10-DIGERATI
² ²
²² ²
Release Info ²
²² Cracker ...... DIGERATI Release-Type.. Regged ²
² Packager...... DIGPACKER Release-Date.. 10/9/2010 ²
² Supplier...... DIGERATI Protection.... License ²
Coder......... DIGERATI OS............ WinALL ²
² ° Company....... Files......... xx/11 °²²
° °²
° URL genome.tugraz.at °²
² ² ² ²
² ²² ° ° ²² ²
±± ² ² ² ² ±±
°° ² ² ² ² °°
² ² Release Notes ² ²
² ² ² ²
² ² ²²² ²
² ° ° ²
² ²
² ²
² High throughput gene expression analysis is becoming more ²
² and more important in many areas of biomedical research. ²
² cDNA microarray technology is one very promising approach ²
² for high throughput analysis and gives the opportunity to ²
² study gene expression patterns on a genomic scale. ²
² Thousands or even tens of thousands of genes can be ²
² spotted on a microscope slide and relative expression ²
² levels of each gene can be determined by measuring the ²
² fluorescence intensity of labeled mRNA hybridized to the ²
² arrays. Hence, microarrays can be used to identify ²
² differentially expressed genes in two samples on a large ²
² scale. Beyond simple discrimination of differentially ²
² expressed genes, functional annotation ²
² guilt-by-association or diagnostic classification ²
² requires the clustering of genes from multiple experiments ²
² into groups with similar expression patterns. Several ²
² clustering techniques were recently developed and applied ²
² to analyze microarray data. ²
² We have developed a platform independent Java package of ²
² tools to simultaneously visualize and analyze a whole set ²
² of gene expression experiments. After reading the data ²
² from flat files several graphical representations of ²
² hybridizations can be generated, showing a matrix of ²
² experiments and genes, where multiple experiments and ²
² genes can be easily compared with each other. Fluorescence ²
² ratios can be normalized in several ways to gain a best ²
² possible representation of the data for further ²
² statistical analysis. We have implemented hierarchical and ²
² non hierarchical algorithms to identify similar expressed ²
² genes and expression patterns, including 1 hierarchical ²
² clustering, 2 k-means, 3 self organizing maps, 4 ²
² principal component analysis, and 5 support vector ²
² machines. More than 10 different kinds of similarity ²
² distance measurements have been implemented, ranging from ²
² simple Pearson correlation to more sophisticated ²
² approaches like mutual information. Moreover, it is ²
² possible to map gene expression data onto chromosomal ²
² sequences. The flexibility, variety of analysis tools and ²
² data visualizations, as well as the free availability to ²
² the research community makes this software suite a ²
² valuable tool in future functional genomic studies. ²
² ²
² ²
² ²
² ²
² ²
² ²
² ²
² ²
² ° ° ²²
² Install Notes ² ²
²² ²
² ²²
²² ²²
² ² ² ²
² 1. Unpack and install the software ²
² 2. Use the following information in serial.txt to register ²
² ²
² ²
² ²
² ²
² ² ² ²
² ² ² ² ² ²
²² ²²²
Mission Statement
² ² A few years ago, DiGERATi emerged onto the scene. ² ²
² ² Focusing on quality rather than quantity, our ² ²
² ² members have successfully tackled some of the toughest ² ²
² challenges in the scene. Working as a closely unified ²
² team we have maintained some of the highest standards ²
² for security, quality, innovation, and comradery in the ²
² scene today. DiGERATi is not one or two hardworking ² ²
² ² persons; it is a force of hardworking people. Respect ² ²
² ²² is not to be demanded; it is to be earned! We look ² ²
² ²² forward to working even harder in the future to continue ² ²
² ²² to earn the respect of our peers. For anyone other than ²² ²
² ² our peers, WE DO NOT EXIST! ²²²
° °²²
² ° ° ²
² ²²² ² ²
²²² ° ° ² ° ° ²²
² ° ° ²°° °² ° ° ²
²² ° ° ²²
²² ° ° ²²
² ²
² Our Respect goes out to ²
² ²
BliZZARD BRD CORE CRD DELIGHT DVT DDU EAT F4CG EMBRACE
HAZE HERETIC LZ0 SHOCK SSG TBE UNDERPL ZWT
² ² Greets to all who work hard help make the scene secure! ² ²
² ² ² ²
² ² A special thanks to those who supported us in the past and ² ²
² ² helped to make us what we are today.Also,a major thanks to ² ²
² those that broke the trail for us but can no longer be ²
² here amongst us. ²
² ²
² Who are the digerati and why are they the cyber elite ? ² ²
² ² They are the doers and thinkers. They are not on the ² ²
² ²² frontier, they are the frontier!!... ² ²
² ²² ² ²
² ²² ²² ²
² ² ² ²²
° °²²
² ° ° ²
² ²²² ² ²
²²² ° ° ² ° ° ²²
² ° ° ²°° °² ° ° ²
²² ° ° ²²
² Yce ²
[安全检测]
★未经过安全检测
[安装测试]
★未经过安装测试，使用者后果自负与本论坛无关。
[免责声明]
★本帖介绍的文本内容转自网络，如有出入则以官方站点公布之信息为准，凡摘自网络相关图文介绍内容的本帖不另行标注出处，原创作者如有异议可提出以便删除。
★关于软件破解及注册机可能被杀毒软件报病毒或间谍木马（若已检测到的则将在帖中特别标注），请自行甄别和取舍，不另行加以解释。
★资源下载后请对文件做必要的安全检测，该下载内容仅限于个人测试学习之用，不得用于商业用途，并且请在下载后24小时内删除。
★各计算机系统环境各不相同，因此不保证该软件完全兼容于你的计算机系统，最终解决软件安装运行问题请联络官方站点寻求相关技术支持。
★凡标注为下载链接转自其他站点的，无法保证资源的供源以及资源本身等情况的完整性和可用性（不可控）。
★资源版权归作者及其公司所有，如果你喜欢，请购买正版。
引用 1. Unpack and install the software
2. Use the following information in serial.txt to register 软件类型：软件 行业软件
软件性质：破解软件
操作系统：Windows
应用平台：Windows
问题反馈： http://genome.tugraz.at/contact.shtml
网站链接： http://genome.tugraz.at/
软件介绍：
Genesis是一款用于基因学方面研究的工具包。
Genesis主要特点如下：
使用灵活，带有多种分析工具，视觉化的数据展示，附带平台独立的Java工具包，可以同时分析并展现一整套基因表达试验。
通过读取普通文件中的数据，Genesis能够生成图形化的分析数据，从而能方便的对多个试验的基因数据进行比较。
GENERAL DESCRIPTION
High throughput gene expression analysis is becoming more and more
important in many areas of biomedical research. cDNA microarray
technology is one very promising approach for high throughput
analysis and gives the opportunity to study gene expression patterns
on a genomic scale. Thousands or even tens of thousands of genes can
be spotted on a microscope slide and relative expression levels of
each gene can be determined by measuring the fluorescence intensity
of labeled mRNA hybridized to the arrays. Hence, microarrays can be
used to identify differentially expressed genes in two samples on a
large scale. Beyond simple discrimination of differentially
expressed genes, functional annotation (guilt-by-association) or
diagnostic classification requires the clustering of genes from
multiple experiments into groups with similar expression patterns.
Several clustering techniques were recently developed and applied to
analyze microarray data.
代码 °
° ²
²² ° ² ° °
²² ²² ²²²² ²
²² ²² ²² ²² ²
²² ²² ° ²² ²² ²² ²
° ² ²² ²² ²²² ²² ²² ²²²² °²
²²² ²²²² ²² ²²² ²² ²² ²²
²²° ²² ²² ² ²² ² ² ²²²²²²² ²²
²² ²²² ²² ² ²² ²²° ²² ²²²
²² ²² ² ²²² ²²²²² ²² ²²²
²²²²² ²² ²² ² ²²²² ²² ²² ²²²²
²²²² ²²² ²²² °
° ° ° ²² °
² ²² ִִִִִִִִִִִִִִִִִִִִִִִִִִִִִִ¿
² ° ²²° ²² ³Don't sweat petty ³ ° ²
²² ²² ²² ³things......or pet sweaty ³ ²²
²² ²² ³things. ³ ²²
²² ְִִִִִִִִִִִִִִִִִִִִִִִִִִִִִִ ²²
²° °²
²° °²
° ²² ²² °
² ²² ²² ²
² ² ° ° ² ²
²² The diGERATi Present ²²
Genesis_v1.7.6.30.09.10-DIGERATI
² ²
²² ²
Release Info ²
²² Cracker ...... DIGERATI Release-Type.. Regged ²
² Packager...... DIGPACKER Release-Date.. 10/9/2010 ²
² Supplier...... DIGERATI Protection.... License ²
Coder......... DIGERATI OS............ WinALL ²
² ° Company....... Files......... xx/11 °²²
° °²
° URL genome.tugraz.at °²
² ² ² ²
² ²² ° ° ²² ²
±± ² ² ² ² ±±
°° ² ² ² ² °°
² ² Release Notes ² ²
² ² ² ²
² ² ²²² ²
² ° ° ²
² ²
² ²
² High throughput gene expression analysis is becoming more ²
² and more important in many areas of biomedical research. ²
² cDNA microarray technology is one very promising approach ²
² for high throughput analysis and gives the opportunity to ²
² study gene expression patterns on a genomic scale. ²
² Thousands or even tens of thousands of genes can be ²
² spotted on a microscope slide and relative expression ²
² levels of each gene can be determined by measuring the ²
² fluorescence intensity of labeled mRNA hybridized to the ²
² arrays. Hence, microarrays can be used to identify ²
² differentially expressed genes in two samples on a large ²
² scale. Beyond simple discrimination of differentially ²
² expressed genes, functional annotation ²
² guilt-by-association or diagnostic classification ²
² requires the clustering of genes from multiple experiments ²
² into groups with similar expression patterns. Several ²
² clustering techniques were recently developed and applied ²
² to analyze microarray data. ²
² We have developed a platform independent Java package of ²
² tools to simultaneously visualize and analyze a whole set ²
² of gene expression experiments. After reading the data ²
² from flat files several graphical representations of ²
² hybridizations can be generated, showing a matrix of ²
² experiments and genes, where multiple experiments and ²
² genes can be easily compared with each other. Fluorescence ²
² ratios can be normalized in several ways to gain a best ²
² possible representation of the data for further ²
² statistical analysis. We have implemented hierarchical and ²
² non hierarchical algorithms to identify similar expressed ²
² genes and expression patterns, including 1 hierarchical ²
² clustering, 2 k-means, 3 self organizing maps, 4 ²
² principal component analysis, and 5 support vector ²
² machines. More than 10 different kinds of similarity ²
² distance measurements have been implemented, ranging from ²
² simple Pearson correlation to more sophisticated ²
² approaches like mutual information. Moreover, it is ²
² possible to map gene expression data onto chromosomal ²
² sequences. The flexibility, variety of analysis tools and ²
² data visualizations, as well as the free availability to ²
² the research community makes this software suite a ²
² valuable tool in future functional genomic studies. ²
² ²
² ²
² ²
² ²
² ²
² ²
² ²
² ²
² ° ° ²²
² Install Notes ² ²
²² ²
² ²²
²² ²²
² ² ² ²
² 1. Unpack and install the software ²
² 2. Use the following information in serial.txt to register ²
² ²
² ²
² ²
² ²
² ² ² ²
² ² ² ² ² ²
²² ²²²
Mission Statement
² ² A few years ago, DiGERATi emerged onto the scene. ² ²
² ² Focusing on quality rather than quantity, our ² ²
² ² members have successfully tackled some of the toughest ² ²
² challenges in the scene. Working as a closely unified ²
² team we have maintained some of the highest standards ²
² for security, quality, innovation, and comradery in the ²
² scene today. DiGERATi is not one or two hardworking ² ²
² ² persons; it is a force of hardworking people. Respect ² ²
² ²² is not to be demanded; it is to be earned! We look ² ²
² ²² forward to working even harder in the future to continue ² ²
² ²² to earn the respect of our peers. For anyone other than ²² ²
² ² our peers, WE DO NOT EXIST! ²²²
° °²²
² ° ° ²
² ²²² ² ²
²²² ° ° ² ° ° ²²
² ° ° ²°° °² ° ° ²
²² ° ° ²²
²² ° ° ²²
² ²
² Our Respect goes out to ²
² ²
BliZZARD BRD CORE CRD DELIGHT DVT DDU EAT F4CG EMBRACE
HAZE HERETIC LZ0 SHOCK SSG TBE UNDERPL ZWT
² ² Greets to all who work hard help make the scene secure! ² ²
² ² ² ²
² ² A special thanks to those who supported us in the past and ² ²
² ² helped to make us what we are today.Also,a major thanks to ² ²
² those that broke the trail for us but can no longer be ²
² here amongst us. ²
² ²
² Who are the digerati and why are they the cyber elite ? ² ²
² ² They are the doers and thinkers. They are not on the ² ²
² ²² frontier, they are the frontier!!... ² ²
² ²² ² ²
² ²² ²² ²
² ² ² ²²
° °²²
² ° ° ²
² ²²² ² ²
²²² ° ° ² ° ° ²²
² ° ° ²°° °² ° ° ²
²² ° ° ²²
² Yce ²
[安全检测]
★未经过安全检测
[安装测试]
★未经过安装测试，使用者后果自负与本论坛无关。
[免责声明]
★本帖介绍的文本内容转自网络，如有出入则以官方站点公布之信息为准，凡摘自网络相关图文介绍内容的本帖不另行标注出处，原创作者如有异议可提出以便删除。
★关于软件破解及注册机可能被杀毒软件报病毒或间谍木马（若已检测到的则将在帖中特别标注），请自行甄别和取舍，不另行加以解释。
★资源下载后请对文件做必要的安全检测，该下载内容仅限于个人测试学习之用，不得用于商业用途，并且请在下载后24小时内删除。
★各计算机系统环境各不相同，因此不保证该软件完全兼容于你的计算机系统，最终解决软件安装运行问题请联络官方站点寻求相关技术支持。
★凡标注为下载链接转自其他站点的，无法保证资源的供源以及资源本身等情况的完整性和可用性（不可控）。
★资源版权归作者及其公司所有，如果你喜欢，请购买正版。