New Fields of Research Defined by Open Science Visionaries

The purpose of an open-science non-profit research startup like DIYgenomics is research innovation.

The value is in being able to propose a unique and visionary research agenda of questions that are forward-looking and not the focus or interest of the institutional research industry.

Research innovation falls into two tiers:

First is preventive medicine questions, ‘medicine that matters to me’ (e.g.; small groups or individuals), and non-pathologies.

More importantly, the second tier is defining completely new fields of research such as athletic performance genomics, social intelligence genomics, cognitive performance genomics, and DIYneuroscience, and making progress on widespread philosophical and societal problems such as the destigmatization of physical and mental health issues, and the reduction of discrimination as a broad social problem.

DIY open-science, crowdsourced health social networks, and community biohacking labs are the early-stage startup/venture capital arm of the expanding preventive medicine ecosystem of health services, and are able to surface projects of interest that can then be pursued at the institutional level as relevant.

Synbio Reformulates the Traditional Scientific Method

Synthetic biology continues to be one of the most wide-spread trends reshaping the conduct of science.

Lauded as the potential ‘transistor of the 21st century’ given its transformative possibilities, synthetic biology is the design and construction of biological devices and systems. It is highly multi-disciplinary, linking biology, engineering, functional design, and computation.

One of the key application areas is metabolic engineering, working with cells to greatly expand their usual production of substances that can then be used for energy, agricultural, and pharmaceutical purposes.

Since the nature of synthetic biology is pro-actively creating de novo biological systems, organisms, and capacities (the opposite of the esprit of the passive characterization of phenomena for which the original scientific method was developed), synbio is reformulating the traditional scientific method.

While it is true that optimizing genetic and regulatory processes within cells can be partially construed under the scientific method, the overall scope of activity and methods are much broader.

Innovating de novo organisms and functionality requires a significantly different scientific methodology than that supported by the traditional scientific method. This includes computational modeling and simulation, engineering practices, feedback loops, automated bio-printing, and a re-conceptualization of science as an endeavor of characterizing and creating.

The New Consciousness: Technology Philosophy learns from Queer Theory

Though they might at first seem unrelated, queer theory connects to technology philosophy in two ways: the general level of the discipline of philosophy and the specificity of content.

First, in the general discipline of philosophy, both queer theory and technology philosophy are areas of innovation in philosophical thought. In thinking innovatively in technology philosophy, it is important to track, understand, and incorporate new developments in philosophical thinking, in this case from the progression of the equality philosophies of decolonialism, feminism, queer theory, and transgender and polyamory rights.

Second, the content of queer theory is of interest to technology philosophy. Some of the relevant topics include:

• Equality Philosophies:  The potential deployment of equality philosophies in a world with a variety of human and non-human intelligences
• Consciousness and its Emergence: The emergence of consciousness in a process of awareness, alterity, and translation which could relate to the waking-up of new forms of consciousness 
• Self-constitution of the Subject: The enlargening understanding of how we are constituted and constitute ourselves as subjects, and how this might change in the future as we have even more interior volition and QS self-direction capability, and at the same time greater competition amongst external influences on the constitution of ourselves as digital subjects with partial or full mindfile upload, where the term subject (currently denoting nicely packaged individual consciousnesses in bodies) could become obsolete 

More information: video, video of text references, video en francais

Venter's Deep Linkage: Microbiome, Synbio, Genomics, and Computing

As usual, Craig Venter’s remarks on April 16, 2013 at UC Berkeley did not disappoint - they were inspirational, informative, and demonstrative of progress. Of note is the multidisciplinarity amongst different branches of his labs’ work, for example using synthetic DNA to perform genomic error correction in stem cell operations, genome transplantation between yeast and bacterial species, and linking microbiome activities to pathology and synthetic biology/biofuel synthesis. Some key points were:

• Microbiome – YASP (yet another sequencing problem) – While the human genome is currently thought to contain about 42,000 genes, the microbiome has 10 million genes across diverse phyla, taxa, and species 
• Biofuel – to obtain engineered algae with the desired phenotype that would be a viable alternative to oil, 300 parameters must be engineered 
• Gene function – even in the minimal genome for Mycoplasma genitalium, there are 50 genes whose function is unknown 
• New gene discovery – so far in general scientific discovery, 80 million genes have been found, 95% from ocean water sampling; again in these ‘design components for the future,’ function is unknown 
• ‘Digital phenotype’ is needed for health advance and big health data stream integration – an extended EMR with standardized transmittable digital data for all manner of phenotypic data, both phenotype 1.0 (e.g.; health history, prescriptions, lab results, etc.) and phenotype 2.0 (e.g.; digital omics profiles like proteomics and metabolomics).

Dollar Van Demos

Easily the phreshest idea from New York’s Internet Week, held in Manhattan June 7-14, was Dollar Van Demos! Dollar Van Demos are a showcase of musicians, rappers, and comedians performing inside a dollar van with real passengers. Numerous Brooklyn-based artists are featured in a collection of videos filmed inside dollar vans as they travel along their usual transportation routes.

The site has new videos from Cocoa Sarai, Tah Phrum Duh Bush, Grey Matter, Zuzuka Poderosa, Kid Lucky, Atlas, BIMB Family, I-John, Top Dolla Raz, Hasan Salaam, illSpokinn, Joya Bravo, Bacardiiiii and Jarel soon!

Figure 1. Example videos from Cocoa Sarai and Top $ Raz

Examining tool complexity

Tools and the science findings they enable evolve in lock-step. Many tools have been quietly transforming into complex entities of their own over the last several years. Exemplar contemporary tools on the landscape include many forms of the microscope, mass spectrometer, chromatograph, flow cytometer, and telescope.

The complex tools of today involve a hardware component together with many layers of software
for operating, enumerating and analyzing. The analytics software layer has become critical as mathematical modeling, simulation, automation, statistical computation and informatics are expected features. For example, the new biology extends traditional enumeration and experimentation with the additional steps of mathematical modeling and software simulation, and building test biological machines in the lab.

The increasing complexity of tools means that it is not possible to just wait for hardware speedups anymore, software is the weakest link (open source collaboration helps but only modestly), mathematical advances have been figuring most prominently and the cultural divide between hard science professionals and computer science, mathematics and statistical experts inhibits progress.

Angel investors drive innovation

The Center for Venture Research at the University of New Hampshire reported that in 2007, angels invested almost as much as venture capitalists in startup companies, $26.0 billion vs. $29.4 billion. Focused on seed and startup stage financings, angels invested in far more firms, 57,120 vs. 3,813 for venture capitalists. Angel investment growth was flat in 2007 vs. 2006 while venture capital investment grew 11%. San Francisco Bay Area angel investors comprised 10% of total angel investment activity. As with venture capital, the top four categories of angel investment in order were software, healthcare, biotech and energy.

Angel investing was once a solitary activity driven by personal networks, the practice has been formalizing in the last several years and there are now over 150 angel investor groups in the U.S. and Canada. The groups typically meet monthly where 3-6 pre-screened companies present to members. Angel investors are not disengaged retirees, 80% continue to be actively involved in the business world. Cleantech and even social venture capital are starting to be interest areas for angel investors.

Angel investors are a critical component of the entrepreneurial ecosystem and should be encouraged and sponsored by communities trying to establish a more innovative environment. For startups, angels can be an important resource for funding, feedback, contacts and exposure. The contribution and impact of angel investors can be expected to grow.

Improving science innovation

To experience most significant scientific advances, humans are dependent on the clunky unreengineered process of science innovation and deployment. Potential improvements to the innovation phase are discussed below.

In the absence of clear feedback loops aligning research investigations with implemented results, scientists can languish in isolated labs for years and the majority do not seem to care whether their findings are useful to or implemented by others. For type A scientists, the in-place incentive system is academic publishing and acknowledgment. Publishing is a codependent phenomenon with scientific publications increasingly exerting influence over the direction of research to generate more interesting reading.


Suggested Improvements

1. Open human knowledge databases
Without yet destabilizing the publishing juggernaut, some progress could be made in releasing already published and unpublishable findings into open databases of human knowledge. There are some early examples of these resources in Physics with ArXiv, the NIH's PubMed and the Earth System Grid for climate research, however there is an opportunity for a new layer of applications to make the information much more accessible to different levels of audiences.

The next three suggestions have to do with creating accountability and a better feedback loop between scientific findings and the use of that information.

2. Quantitative values attached to findings
A system of quantitative values could be applied to research so that findings and scientists could be measured and compared. Supervisors, peers and industry colleagues could rank findings based on a variety of parameters. Unpublishable and null findings would also be incorporated into the valuation program.

3. Annual performance reviews for scientists
The rigor of quarterly goal setting and review, 360 degree feedback and other performance evaluation metrics implemented decades ago in the business environment should also be de rigueur in the scientific community. Performance metrics would be a good start, incorporating what are now standard corporate principles of leadership, communication and management science to reduce subjectivity and otherwise improve scientific working environments would also be helpful.

4. Broader scientific mindset
The most successful scientists have been those who have perceived their roles as not the mere discovers and handers-off of the Truth but also as being responsible for rendering their findings implementable by others. Emphasizing full realization of pursuits and results from a more service-driven than ego-driven mindset could also produce better results more quickly.

Immobile Mobile Platform

Class I Innovation
The common theme of recently Tier-A venture-backed mobile companies Flurry, SoonR and Dash, and social networking platform ccube is that they are not really mobile. The main work occurs at the stationary platform which is oh, by the way downloaded to a mobile device and in some cases best used with a [power-consuming] preferably always-on tether to the stationary platform.

Certainly there is use for these services for email and news via text/SMS plans for mainstream non-smart phones without Internet plans, desktop synchronization and next-gen GPS with web-based local search functionality but worrying about creating cool ajaxy websites for the stationary platform does not truly extend the mobile platform.

Class II Innovation
Class II innovations involve a different mindset - thinking of the mobile device as an asset not a liability and thinking of the mobile device and devices as a true platform. The idea is to accentuate and extend the mobile platform and innovate new applications and services for use on the go.

Some of these could include more sensor-based services regarding the local setting, permissioned messaging from local merchants via text, Internet or voice (push a hotkey to have a service call you with the name and details of nearby wifi cafes, 3-star restaurants with immediate availability). That the phone is a phone is often forgotten for efficient asynchronous information delivery. Distribute platform services could include accessing anonymized data from other nearby phones which have made similar requests via push or pull, or using other crowd-search smarts for similar information.

Mobile is inherently multidisciplinary and innovations in hardware, integration and other software areas such as speech recognition as they arrive will likely continually redefine the mobile platform and trigger new waves of services development. Presumably in the not too distant future, mobile and stationary should be somewhat meaningless distinctions (like digital and biological intelligence) when considering the ubiquitous wide-band continually communicating computing grid.

Innovation Addiction

Things are changing so rapidly and in so many ways now in the early 2000s that one can actually pursue or focus on innovation or change as an entity unto itself. Since so much innovation occurs in technology, it is possible to mistake technology as the critical part, but technology is just an interesting substrate, the innovation is the key part.

Even though technology is maybe just the most active substrate, there is some causality at work in that the minds and value systems of the technology world are more geared to the pureness of thought and ideas, openness, inclusion and creativity in the way that other substrates such as business and politics are not.

Why is innovation so addictive? There are at least two reasons: innovation's inherent dynamism and capacity for transformation. Any phenomenon with dynamism and movement is intriguing, think of fire or coastal tides for example. Movement implies growth, newness, regeneration, the cycles and patterns of life. The property of capacity for change is also captivating, the unstated promise of progress, improvements to life, more effective ways of perceiving, of interacting, of being and doing and living in this world and others. Innovation is exciting because it suggests new experience.

Tools are Imperative

A continuation on the theme of humans being better innovators...

Creating new tools is often a key step in stimulating innovation. To do the innovation one wants, one may need to develop better tools to help. These tools in turn can beget an entirely new tier of innovation in a virtuous upward progression. A metaphor could be applied in some cases that the tools ARE the innovation much like Marsh McLuhan's medium IS the message.

Freeman Dyson cites the important example of astronomers, who build their own tools, being farther up the development curve than biotechnologists, who rely on others to build the tools they use. There appears to be a fundamental linkage and relationship between the tools and the innovation.

To innovate, we can focus on improving and creating tools. We can think of the areas of our lives and the tools we currently use there and problems we'd like to solve and what tools or solutions, objects, processes, etc. would do this and make life easier and better. We can dare to dream, create and invent!