Biotechnology - Genomic and Proteomics - Revision history

WikiSysop: /* Resources */

2010-10-16T21:10:58Z

Resources

← Older revision		Revision as of 21:10, 16 October 2010
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	== Resources ==		== Resources ==
	~~=== [[Biotechnology - Genomic and Proteomics/Bibliography by Resource Type \| Bibliography by Resource Type]] ===~~
	=== [[Biotechnology - Genomic and Proteomics/Bibliography by Research Question \| Bibliography by Research Question]] ===		=== [[Biotechnology - Genomic and Proteomics/Bibliography by Research Question \| Bibliography by Research Question]] ===
	=== [[Biotechnology - Genomic and Proteomics/Others\|Others]]===		=== [[Biotechnology - Genomic and Proteomics/Others\|Others]]===



	==Navigation==		==Navigation==

	[[Main Page]]		[[Main Page]]

WikiSysop: /* Study of the field */

2010-05-06T04:02:03Z

Study of the field

← Older revision		Revision as of 04:02, 6 May 2010
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	== Study of the field ==		== Study of the field ==

	Analysis of the field with basis on [~~https://cyber.law.harvard.edu/commonsbasedresearch/Field_Research_Methodology Field Research Methodology~~]		Analysis of the field with basis on [[ICP Main Questions]]

	# [[Overview of Economics of Intellectual Property in BGP]]		# [[Overview of Economics of Intellectual Property in BGP]]

WikiSysop: /* Genomics */

2010-05-04T19:25:35Z

Genomics

← Older revision		Revision as of 19:25, 4 May 2010
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	===Genomics===		===Genomics===
	*[[Sage - A Merck Project]]		*[[Sage - A Merck Project]]
	*[[A brief history of license practices in BGP - the case of PCR]]		* [[History PCR]]
			**A brief history of license practices in BGP - the case of PCR

	===[[Diagnostic Kits]]===		===[[Diagnostic Kits]]===
	===[[Vaccines]]===		===[[Vaccines]]===

WikiSysop: /* Visualization */

2010-04-23T04:31:49Z

Visualization

← Older revision		Revision as of 04:31, 23 April 2010
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	=== [[Biotechnology - Genomic and Proteomics/Others\|Others]]===		=== [[Biotechnology - Genomic and Proteomics/Others\|Others]]===

	~~==Visualization==~~

	~~[[Image:BGP Business flow 3.jpg]]~~

	==Navigation==		==Navigation==

	[[Main Page]]		[[Main Page]]

WikiSysop: /* Study of the field */

2010-04-20T05:13:09Z

Study of the field

← Older revision		Revision as of 05:13, 20 April 2010
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	# [[IP Profile of Associations in BGP]]		# [[IP Profile of Associations in BGP]]
	# [[Commons based cases in BGP]]		# [[Commons based cases in BGP]]
	# [[Peer-Production ~~Business models~~ in BGP]]		# [[Peer-Production Models in BGP]]
	# [[Open Business models in BGP]]		# [[Open Business models in BGP]]

WikiSysop: /* Proteomics */

2010-04-20T02:50:50Z

Proteomics

← Older revision		Revision as of 02:50, 20 April 2010
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	For protein tools, antibodies are the biggest category. We can classify all sorts of antibodies for specific study like cytokines, neurotrophins, etc. There is also a growing system for protein expression like gene expression that depends on antibodies, but also now can use all sorts of genomic tools. So the genomic tools are now becoming proteomic tools as well. Also, access to the same stem cells and mice is essential if the research is going to translate to cures. It will be interesting to look and see if the same desire for treating the outputs of research as inputs to new research we saw in the fundamental genomic data space apply here.<br>		For protein tools, antibodies are the biggest category. We can classify all sorts of antibodies for specific study like cytokines, neurotrophins, etc. There is also a growing system for protein expression like gene expression that depends on antibodies, but also now can use all sorts of genomic tools. So the genomic tools are now becoming proteomic tools as well. Also, access to the same stem cells and mice is essential if the research is going to translate to cures. It will be interesting to look and see if the same desire for treating the outputs of research as inputs to new research we saw in the fundamental genomic data space apply here.<br>
	Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>		Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>
	We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.		We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.<br>
	[[Image:ProteomicsIP.jpg]]<br>		[[Image:ProteomicsIP.jpg]]<br>
	PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.		PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.

WikiSysop: /* Proteomics */

2010-04-20T02:50:31Z

Proteomics

← Older revision		Revision as of 02:50, 20 April 2010
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	The science of genomics is focused on the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine‐scale genetic mapping efforts to determine the activity and function of genes. Genomic scientists produce genetic, pathway, and functional information analysis about the genome in attempts to place the DNA code in context inside living beings, typically in order to improve human health or advance agricultural technology.<br>		The science of genomics is focused on the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine‐scale genetic mapping efforts to determine the activity and function of genes. Genomic scientists produce genetic, pathway, and functional information analysis about the genome in attempts to place the DNA code in context inside living beings, typically in order to improve human health or advance agricultural technology.<br>
	The first techniques that can be related to genomics were the development of sequencing, genome mapping, data storage, and bioinformatics analyses in the 1970‐1980s. This period also marks the birth of the first biotechnology industries in the USA. Amgen and Genentech are the oldest examples still in the market and are models for other startups in terms of business models. The high uncertainty and asymmetry of information characteristic of the biotechnology industry transformed the field, from a commercial perspective into an archipelago of high‐specialized islands of knowledge. Collaborations inside the industry have since that time been characterized by the “big deal” involving a complex transfer of IP, future royalties, data, investment, and employee sharing. Such collaborations are rarely open to outside parties and are themselves asymmetrical in their treatment of property.		The first techniques that can be related to genomics were the development of sequencing, genome mapping, data storage, and bioinformatics analyses in the 1970‐1980s. This period also marks the birth of the first biotechnology industries in the USA. Amgen and Genentech are the oldest examples still in the market and are models for other startups in terms of business models. The high uncertainty and asymmetry of information characteristic of the biotechnology industry transformed the field, from a commercial perspective into an archipelago of high‐specialized islands of knowledge. Collaborations inside the industry have since that time been characterized by the “big deal” involving a complex transfer of IP, future royalties, data, investment, and employee sharing. Such collaborations are rarely open to outside parties and are themselves asymmetrical in their treatment of property.
	[[Image:GenomicsIP.jpg]]		[[Image:GenomicsIP.jpg]]<br>
	PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.		PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.
	===Proteomics===		===Proteomics===
Line 61:		Line 61:
	Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>		Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>
	We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.		We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.
	[[Image:~~Proteomics~~.jpg]]<br>		[[Image:ProteomicsIP.jpg]]<br>
	PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.		PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.

WikiSysop: /* Proteomics */

2010-04-20T02:49:16Z

Proteomics

← Older revision		Revision as of 02:49, 20 April 2010
Line 61:		Line 61:
	Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>		Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>
	We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.		We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.
	[[Image:Proteomics.jpg]]		[[Image:Proteomics.jpg]]<br>
	PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.		PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.

WikiSysop: /* Genomics */

2010-04-20T02:48:56Z

Genomics

← Older revision		Revision as of 02:48, 20 April 2010
Line 55:		Line 55:
	The first techniques that can be related to genomics were the development of sequencing, genome mapping, data storage, and bioinformatics analyses in the 1970‐1980s. This period also marks the birth of the first biotechnology industries in the USA. Amgen and Genentech are the oldest examples still in the market and are models for other startups in terms of business models. The high uncertainty and asymmetry of information characteristic of the biotechnology industry transformed the field, from a commercial perspective into an archipelago of high‐specialized islands of knowledge. Collaborations inside the industry have since that time been characterized by the “big deal” involving a complex transfer of IP, future royalties, data, investment, and employee sharing. Such collaborations are rarely open to outside parties and are themselves asymmetrical in their treatment of property.		The first techniques that can be related to genomics were the development of sequencing, genome mapping, data storage, and bioinformatics analyses in the 1970‐1980s. This period also marks the birth of the first biotechnology industries in the USA. Amgen and Genentech are the oldest examples still in the market and are models for other startups in terms of business models. The high uncertainty and asymmetry of information characteristic of the biotechnology industry transformed the field, from a commercial perspective into an archipelago of high‐specialized islands of knowledge. Collaborations inside the industry have since that time been characterized by the “big deal” involving a complex transfer of IP, future royalties, data, investment, and employee sharing. Such collaborations are rarely open to outside parties and are themselves asymmetrical in their treatment of property.
	[[Image:GenomicsIP.jpg]]		[[Image:GenomicsIP.jpg]]
			PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.
			===Proteomics===
			In terms of data and narrative outputs, proteomics is very similar. There is fundamental and observational data, though there is no “human proteome project” like the HGP to serve as an aggregating actor for commons based efforts. There are many smaller efforts that we can study including databases in structural genomics and protein data.<br>
			For protein tools, antibodies are the biggest category. We can classify all sorts of antibodies for specific study like cytokines, neurotrophins, etc. There is also a growing system for protein expression like gene expression that depends on antibodies, but also now can use all sorts of genomic tools. So the genomic tools are now becoming proteomic tools as well. Also, access to the same stem cells and mice is essential if the research is going to translate to cures. It will be interesting to look and see if the same desire for treating the outputs of research as inputs to new research we saw in the fundamental genomic data space apply here.<br>
			Some other kinds of protein tech would include high throughput screening array technology (the robots that test drugs against proteins) and software tools: structure prediction, identification, properties, alignment. Proteomics research is very intensive in terms of computation and software (much more complex than genomics – more similar in some ways to climate change and weather modeling in terms of complexity).<br>
			We should probably expect to discuss the impact of patents as biomarker / diagnostic marker. Gene patents haven't had the expected impact of anticommons, but protein patents are extremely valuable and frequently enforced.
			[[Image:Proteomics.jpg]]
			PD=Public Domains; C = Copyright; P = Patents; TS = Trade Secret; Con = Contracts, including Material Transfer Agreements; N = Community construed norms.

	===Deprioritized Market Segments===		===Deprioritized Market Segments===

WikiSysop: /* Genomics */

2010-04-20T02:45:11Z

Genomics

← Older revision		Revision as of 02:45, 20 April 2010
Line 54:		Line 54:
	The science of genomics is focused on the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine‐scale genetic mapping efforts to determine the activity and function of genes. Genomic scientists produce genetic, pathway, and functional information analysis about the genome in attempts to place the DNA code in context inside living beings, typically in order to improve human health or advance agricultural technology.<br>		The science of genomics is focused on the study of the genomes of organisms. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine‐scale genetic mapping efforts to determine the activity and function of genes. Genomic scientists produce genetic, pathway, and functional information analysis about the genome in attempts to place the DNA code in context inside living beings, typically in order to improve human health or advance agricultural technology.<br>
	The first techniques that can be related to genomics were the development of sequencing, genome mapping, data storage, and bioinformatics analyses in the 1970‐1980s. This period also marks the birth of the first biotechnology industries in the USA. Amgen and Genentech are the oldest examples still in the market and are models for other startups in terms of business models. The high uncertainty and asymmetry of information characteristic of the biotechnology industry transformed the field, from a commercial perspective into an archipelago of high‐specialized islands of knowledge. Collaborations inside the industry have since that time been characterized by the “big deal” involving a complex transfer of IP, future royalties, data, investment, and employee sharing. Such collaborations are rarely open to outside parties and are themselves asymmetrical in their treatment of property.		The first techniques that can be related to genomics were the development of sequencing, genome mapping, data storage, and bioinformatics analyses in the 1970‐1980s. This period also marks the birth of the first biotechnology industries in the USA. Amgen and Genentech are the oldest examples still in the market and are models for other startups in terms of business models. The high uncertainty and asymmetry of information characteristic of the biotechnology industry transformed the field, from a commercial perspective into an archipelago of high‐specialized islands of knowledge. Collaborations inside the industry have since that time been characterized by the “big deal” involving a complex transfer of IP, future royalties, data, investment, and employee sharing. Such collaborations are rarely open to outside parties and are themselves asymmetrical in their treatment of property.
	[[Image:~~Example~~.jpg]]		[[Image:GenomicsIP.jpg]]

	===Deprioritized Market Segments===		===Deprioritized Market Segments===