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Aubrey de Grey – Artificial Organs as Replacement Parts to aid in Defeating Aging

Aubrey de Grey discusses using artificial organs and synthetic devices as replacement parts to aid in defeating aging. (Also see this interview where Aubrey discusses some of the various approaches that SENS therapy will likely be delivered.)


Replacing a failing organ with a healthy one can sidestep the need for the various SENS therapies for that organ only – however there are two limitations – 1) much of the body is made up of non-transplantable organs, 2) transplanting organs or tissue engineering involves invasive surgery, something that involves risks if it is done too much.
Organ transplantation/Tissue engineering is useful today and will be useful when early forms of SENS delivery become available – however there will continue to be a very high priority in approaches that mitigate the need for invasive organ transplantation.
Non-biological organs are useful today – for instance the cochlear implant – and there will continue to be a place for them. Though in the long run biological organs will likely work more effectively because they are ‘evolved’ for that purpose.


Aubrey de Grey is the chief science officer of the SENS Research Foundation, which is a 501(c)(3) public charity that is transforming the way the world researches and treats age-related disease.

The research SENS funds at universities around the world and at SENS own Research Center uses regenerative medicine to repair the damage underlying the diseases of aging. The goal of SENS is to help build the industry that will cure these diseases.


Aubrey de Grey was interviewed by Adam Ford in 2012.

Here is a playlist of all the interview sections:

Be Greedy For The Most Good You Can Do – Kerry Vaughan – EA Global Melbourne 2015

Filmed at EA Global Melbourne 2015 Slides of talk are here
Kerry Vaughan discusses:
What is effective altruism? what is it’s history? what isn’t EA? and how to succeed at being an effective altruist.
Approaches to doing good include:
– Being Skeptical – using the case study of play pumps in africa – hoping to utilize the renewable energy of children playing – on the surface it looked like a good idea, but unfortunately it didn’t work – so be skeptical
– Changing your Mind – you can score social points in the EA movement by changing your mind – so yay! Moving beyond entrenched beliefs to better ways of thinking leads decision making – do change your mind, update your beliefs when there is evidence to support you doing so
– Do it! – when you find out better approaches to being altruistic, actually follow up and do it – without getting too involved in theorizing whether you have a moral obligation to solve the problem, just go solve it
– 3 strands to the history of EA – Peter Singer’s work, Holden Karlovsky and Elie Hassenfeld at Give Well, the rationalist movement (inc CFAR)
Kerry then discusses the growth of the EA movement.
Approaches to EA based on evidence (empiricism) and also strong philosophical arguments (esp in the absence of evidence – for instance with Existential Risks or far future scenarios)
How to succeed at EA Global: get help, and make radical life change.

Kerry Vaughan - Be Greedy for the Most Good - EA Global Melbourne 2015 - Effective Altruism 2

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Superlongevity – Mini Documentary

Short documentary on longevity science going mainstream and surrounding public opinion – with some key folk in the transhumanist movement discussing the issues around aging and the state of play, how to think rationally about aging and longevity medicine, media performance, common objections to longevity technology, advocacy, how the public may come to terms with and ultimately accept longevity technology.

I hope to be developing this documentary further in the near future.

Starring : Aubrey de Grey, Max More, Michael Shermer, George Dvorsky, David Pearce and Ramez Naam.

Ramez NaamRamez Naam is a professional technologist and science fiction writer. He was involved in the development of widely used software products such as Microsoft Internet Explorer and Microsoft Outlook. His last role at Microsoft was as a Partner Group Program Manager in Search Relevance for Live Search.  Naam currently holds a seat on the advisory board of the Acceleration Studies Foundation, is a member of the World Future Society, a Senior Associate of the Foresight Institute, and a fellow of the Institute for Ethics and Emerging Technologies.

MAx1Max More is a philosopher and futurist who writes, speaks, and consults on advanced decision-making about emerging technologies.  Founder of the Extropy Institute, Max More has written many articles espousing the philosophy of transhumanism and the transhumanist philosophy of Extropianism, most importantly his Principles of Extropy.  At the start of 2011, Max More became president and CEO of the Alcor Life Extension Foundation, an organization he joined in 1986.

Michael-Shermer1-500x500_cMichael Brant Shermer is a science writer, historian of science, founder of The Skeptics Society, and Editor in Chief of its magazine Skeptic, which is largely devoted to investigating pseudoscientific and supernatural claims. The Skeptics Society currently has over 55,000 members. Shermer also engages in debates on topics pertaining to pseudoscience and religion in which he emphasizes scientific skepticism.

David Pearce - Healesville SanctuaryDavid Pearce is a British philosopher who promotes the idea that there exists a strong ethical imperative for humans to work towards the abolition of suffering in all sentient life. His book-length internet manifesto The Hedonistic Imperative outlines how technologies such as genetic engineering, nanotechnology, pharmacology, and neurosurgery could potentially converge to eliminate all forms of unpleasant experience among human and non-human animals, replacing suffering with gradients of well-being, a project he refers to as “paradise engineering”.

aubreyeagleAubrey de Grey is an English author and biomedical gerontologist, currently the Chief Science Officer of the SENS Research Foundation. He is editor-in-chief of the academic journal Rejuvenation Research, author of The Mitochondrial Free Radical Theory of Aging (1999) and co-author of Ending Aging (2007). He is known for his view that medical technology may enable human beings alive today to live indefinitely

George Dvorsky San FranGeorge Dvorsky is a Canadian bioethicist, transhumanist, and futurist. He is a contributing editor at io9 and producer of the Sentient Developments blog and podcast. Dvorsky currently serves as Chair of the Board for the Institute for Ethics and Emerging Technologies (IEET) and is the founder and chair of the IEET’s Rights of Non-Human Persons Program, a group that is working to secure human-equivalent rights and protections for highly sapient animals.

 


 

All footage footage is either my own, is news under ‘fair use’ (in line with the 4 factors of fair use) or I have permission from the owners.

Stay tuned, as there will be further updates.

Current version: v1.0 (video)

Previous versions:
v0.91 (video)
v0.9 (video)

Superlongevity---triangles-circle1

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Lawrence Krauss – An update on Cosmology – How Big Bang Gravitational Waves Could Revolutionize Physics!

Lawrence Krauss – An update on Cosmology and thoughts on Education – Cosmologist with Attitude

How Big Bang Gravitational Waves Could Revolutionize Physics! Lawrence is well known for his critical thinking and promotion of science. He has appeared on Q & A among other shows. Lawrence Krauss is Director of the ASU Origins Project at Arizona State University and Foundation Professor in the School of Earth and Space Exploration and the Department of Physics.
Described by Scientific American as a unique scientific ‘public intellectual’, Krauss is a renowned theoretical physicist as well as one of the most well-known advocates for science worldwide. In addition to over 300 scientific publications, He has written nine books for a general audience, including the international bestsellers The Physics of Star Trek and A Universe From Nothing, with translations into over 20 languages. His research has focused on the intersection on cosmology and elementary particle physics, including general relativity and quantum gravity, the early universe, the origin of mass, neutrino astrophysics, and the long term future of the universe. He is the winner of numerous international awards, and is the only physicist to have received the major awards from all three US physics societies. In 2012, he was awarded The National Science Board’s Public Service Award for his many contributions. He frequently appears on TV and radio and contributes to newspapers and magazines, and is the subject of a new full-length feature film, The Unbelievers, which follows Krauss and Richard Dawkins around the world as they discuss science and reason.

The evening was put on by the Vic Skeptics & was held at Graduate House Conference Centre, 220 Leicester Street Carlton on Friday 29 August with proceedings beginning at 6:30pm.

Lawrence Krauss Vic Skeptics

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Lawrence Krauss Video Image

Vernor Vinge on the Technological Singularity

What is the Singularity? Vernor Vinge speaks about technological change, offloading cognition from minds into the environment, and the potential of Strong Artificial Intelligence.

Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.” – “The Coming Technological SingularityVernor Vinge 1993

Vernor Vinge popularised and coined the term “Technological Singularity” in his 1993 essay “The Coming Technological Singularity“, in which he argues that the creation of superhuman artificial intelligence will mark the point at which “the human era will be ended,” such that no current models of reality are sufficient to predict beyond it.

courtesy of the Imaginary Foundation

courtesy of the Imaginary Foundation

Vinge published his first short story, “Bookworm, Run!”, in the March 1966 issue of Analog Science Fiction, then edited by John W. Campbell. The story explores the theme of artificially augmented intelligence by connecting the brain directly to computerised data sources. He became a moderately prolific contributor to SF magazines in the 1960s and early 1970s. In 1969, he expanded two related stories, (“The Barbarian Princess”, Analog, 1966 and “Grimm’s Story”, Orbit 4, 1968) into his first novel, Grimm’s World. His second novel, The Witling, was published in 1975.

Vinge came to prominence in 1981 with his novella True Names, perhaps the first story to present a fully fleshed-out concept of cyberspace, which would later be central to cyberpunk stories by William Gibson, Neal Stephenson and others.

 

Vernor Vinge

Image Courtesy – Long Now Foundation

Automating Science: Panel – Stephen Ames, John Wilkins, Greg Restall, Kevin Korb

A discussion among philosophers, mathematicians and AI experts on whether science can be automated, what it means to automate science, and the implications of automating science – including discussion on the technological singularity.

– implementing science in a computer – Bayesian methods – most promising normative standard for doing inductive inference
– vehicle : causal Bayesian networks – probability distributions over random variables showing causal relationships
– probabilifying relationships – tests whose evidence can raise the probability

05:23 does Bayesianism misrepresent the majority of what people do in science?

07:05 How to automate the generation of new hypotheses?
– Is there a clean dividing line between discovery and justification? (Popper’s view on the difference between the context of discovery and context of justification) Sure we discuss the difference between the concepts – but what is the difference between the implementation?

08:42 Automation of Science from beginning to end: concept formation, discovery of hypotheses, developing experiments, testing hypotheses, making inferences … hypotheses testing has been done – through concept formation is an interestingly difficult problem

Panel---Automating-Science-and-Artificial-Intelligence---Kevin-Korb,-Greg-Restall,-John-Wilkins,-Stephen-Ames-1920x10839:38 – does everyone on the panel agree that automation of science is possible? Stephen Ames: not yet, but the goal is imminent, until it’s done it’s an open question – Kevin/John: logically possible, question is will we do it – Greg Restall: Don’t know, can there be one formal system that can generate anything classed as science? A degree of open-endedness may be required, the system will need to represent itself etc (Godel!=mysticism, automation!=representing something in a formal deductive theory)

13:04 There is a Godel theorem that applies to a formal representation for automating science – that means that the formal representation can’t do everything – therefore what’s the scope of a formal system that can automate science? What will the formal representation and automated science implementation look like?

14:20 Going beyond formal representations to automate science (John Searle objects to AI on the basis of formal representations not being universal problem solvers)

15:45 Abductive inference (inference to the best explanation) – & Popper’s pessimism about a logic of discovery has no foundation – where does it come from? Calling it logic (if logic means deduction) is misleading perhaps – abduction is not deductive, but it can be formalised.

17:10 Some classified systems fall out of neural networks or clustering programs – Google’s concept of a cat is not deductive (IFAIK)

19:29 Map & territory – Turing Test – ‘if you can’t tell the difference between the model and the real system – then in practice there is no difference’ – the behavioural test is probably a pretty good one for intelligence

22:03 Discussion on IBM Watson on Jeopardy – a lot of natural language processing but not natural language generation

24:09 Bayesianism – in mathematics and in humans reasoning probabilistically – it introduced the concept of not seeing everything in black and white. People get statistical problems wrong often when they are asked to answer intuitively. Is the technology likely to have a broad impact?

26:26 Human thinking, subjective statistical reasoning – and the mismatch between the public communicative act often sounding like Boolean logic – a mismatch between our internal representation and the tools we have for externally representing likelihoods
29:08 Low hanging fruit in human communication probabilistic reasoning – Bayesian nets and argument maps (Bayesian nets strengths between premises and conclusions)

29:41 Human inquiry, wondering and asking questions – how do we automate asking questions (as distinct from making statements)? Scientific abduction is connected to asking questions – there is no reason why asking questions can’t be automated – there is contrasted explanations and conceptual space theory where you can characterise a question – causal explanation using causal Bayesian networks (and when proposing an explanation it must be supported some explanatory context)

32:29 Automating Philosophy – if you can automate science you can automate philosophy –

34:02 Stanford Computational Metaphysics project (colleagues with Greg Restall) – Stanford Computational Metaphysics project – formalization of representations of relationships between concepts – going back to Leibniz – complex notions can be boiled down to simpler primitive notions and grinding out these primitive notions computationally – they are making genuine discoveries
Weak Reading: can some philosophy be automated – yes
Strong Reading of q: can All of philosophy be automated? – there seem to be some things that count as philosophy that don’t look like they will be automated in the next 10 years

35:41 If what we’re is interested in is to represent and automate the production of reasoning formally (not only to evaluate), as long as the domain is such that we are making claims and we are interested in the inferential connections between the claims, then a lot of the properties of reasoning are subject matter agnostic.

36:46 (Rohan McLeod) Regarding Creationism is it better to think of it as a poor hypothesis or non-science? – not an exclusive disjunct, can start as a poor hypothesis and later become not-science or science – it depends on the stage at the time – science rules things out of contention – and at some point creationism had not been ruled out

38:16 (Rohan McLeod) Is economics a science or does it have the potential to be (or is it intrinsically not possible for it to be a science) and why?
Are there value judgements in science? And if there are how do you falsify a hypothesis that conveys a value judgement? physicists make value judgements on hypothesis “h1 is good, h2 is bad” – economics may have reducible normative components but physics doesn’t (electrons aren’t the kinds of things that economies are) – Michael ??? paper on value judgements – “there is no such thing as a factual judgement that does not involve value” – while there are normative components to economics, it is studied from at least one remove – problem is economists try to make normative judgements like “a good economy/market/corporation will do X”

42:22 Problems with economics – incredibly complex, it’s hard to model, without a model exists a vacuum that gets filled with ideology – (are ideologies normative?)

42:56 One of the problems with economics is it gets treated like a natural system (in physics or chemistry) which hides all the values which are getting smuggled in – commitments and values which are operative and contribute to the configuration of the system – a contention is whether economics should be a science (Kevin: Yes, Stephen: No) – perhaps economics could be called a nascent science (in the process of being born)

44:28 (James Fodor) Well known scientists have thought that their theories were implicit in nature before they found them – what’s the role of intuition in automating science & philosophy? – need intuitions to drive things forward – intuition in the abduction area – to drive inspiration for generating hypothesis – though a lot of what get’s called intuition is really the unconscious processing of a trained mind (an experienced driver doesn’t have to process how to drive a car) – Louis Pasteur’s prepared mind – trained prior probabilities

46:55 The Singularity – disagreement? John Wilkins suspects it’s not physically possible – Where does Moore’s Law (or its equivalents in other hardware paradigms) peter out? The software problem could be solved near or far. Kevin agrees with I.J. Good – recursively improving abilities without (obvious) end (within thermodynamic limits). Kevin Korb explains the intelligence explosion.

50:31 Stephen Ames discusses his view of the singularity – but disagrees with uploading on the grounds of needing to commit to philosophical naturalism

51:52 Greg Restall mistrusts IT corporations to get uploading right – Kevin expresses concerns about using star-trek transporters – the lack of physical continuity. Greg discusses theories of intelligence – planes fly as do birds, but planes are not birds – they are differing

54:07 John Wilkins – way too much emphasis is put on propositional knowledge and communication in describing intelligence – each human has roughly the same amount of processing power – too much rests on academic pretense and conceit.

54:57 The Harvard Rule – under conditions of consistent lighting, feeding etc – the organism will do as it damn well pleases. But biology will defeat simple models.. Also Hulls rule – no matter what the law in biology is there is an exception (inc Hull’s law) – so simulated biology may be difficult. We won’t simulate an entire organism – we can’t simulate a cell. Kevin objects

58:30 Greg R. says simulations and models do give us useful information – even if we isolate certain properties in simulation that are not isolated in the real world – John Wilkins suggests that there will be a point where it works until it doesn’t

1:00:08 One of the biggest differences between humans and mice is 40 million years of evolution in both directions – the problem is in evo biol is your inductive projectability – we’ve observed it in these cases, therefore we expect it in this – it fades out relatively rapidly in direct disproportion to the degree of relatedness

1:01:35 Colin Kline – PSYCHE – and other AI programs making discoveries – David Chalmers have proposed the Hard Problem of Consciousness – pZombies – but we are all pZombies, so we will develop systems that are conscious because there is to such thing as consciousness. Kevin is with Dennet – info processing functioning is what consciousness supervenes upon
Greg – concept formation in systems like PSYCHE – but this milestone might be very early in the development of what we think of as agency – if the machine is worried about being turned off or complains about getting board, then we are onto something

Aubrey de Grey – Engaging the Disengaged

There is likely a lot of mileage in engaging the disengaged in untapped support for more efficient progress in regenerative medicine. We need to talk about the familiar and positive aspects of rejuvenation medicine!

Aging issues have appeared in the media a lot recently – all to often the narrative is skewed in the direction of sci-fi sounding future scenarios, and are embedded in sensationalized media stunts, to the effect that for many the ideas ‘go out one ear and out the other’ – the people whom are currently disengaged forget about rejuvenation medicine and loose interest when they hear about the latest patch for their iphone.

There are a lot more people out there in the world besides transhumanists who have resources and energy to transform into meaningful progress in the science of rejuvenation biotechnology.
People also get fixated on long term Malthusian visions or the pseuodoscientific and religious connotations of words like ‘immortality’ and loose sight of the fact that SENS and others are working on _health_.

History shows a bleak picture, but the further back we go, the worse it seems. It seems civilization is getting better at healthy living into older age – now it really is a priority to get better at getting better – effective aging, so to speak.
There is so much in the world to do – many people grow old and unable to do the things they want to do before they have finished doing much of what they want to do. Live is precious – it’s an imperative that we focus on giving people extra healthy life-time for them to do more of the things they love to do.

Aubrey-de-Grey-Engaging-the-Disengaged

The main thing that people misunderstanding is the actual relationship between aging and the diseases of old age – and this is largely the fault of gerontologists….people would go out and say, all the time, ‘Aging is not a disease’ – that’s not useful. Ultimately it’s very counter productive. What happened was people would think to themselves ‘well ok then, aging is this natural thing that’s never going to be amenable to medical intervention, because it’s not a disease – and also because it’s not a disease, then why should we care about it?’ – so it was absolutely the wrong thing to be saying… it’s even more the wrong thing to be saying because it’s not even true. Aubrey de Grey

Aubrey de Grey is the chief science officer of the SENS Research Foundation, which is a 501(c)(3) public charity that is transforming the way the world researches and treats age-related disease.

The research SENS funds at universities around the world and at SENS own Research Center uses regenerative medicine to repair the damage underlying the diseases of aging. The goal of SENS is to help build the industry that will cure these diseases.


Aubrey de Grey was interviewed by Adam Ford in 2012.

Here is a playlist of all the interview sections:

Peter Singer – Ethics, Utilitarianism & Effective Altruism

Peter Singer at UMMS - Ethics Utilitarianism Effective Altruism
Peter Singer discusses Effective Altruism, including Utilitarianism as a branch of Ethics. Talk was held as a joint event between the University of Melbourne Secular Society and Melbourne University Philosophy Community.

Is philosophy, as a grounds to help decide how good an action is, something you spend time thinking about?

Audio of Peter’s talk can be found here at the Internet Archive.

In his 2009 book ‘The Life You Can Save’, Singer presented the thought experiment of a child drowning in a pond before our eyes, something we would all readily intervene to prevent, even if it meant ruining an expensive pair of shoes we were wearing. He argued that, in fact, we are in a very similar ethical situation with respect to many people in the developing world: there are life-saving interventions, such as vaccinations and clean water, that can be provided at only a relatively small cost to ourselves. Given this, Singer argues that we in the west should give up some of our luxuries to help those in the world who are most in need.

If you want to do good, and want to be effective at doing good, how do you go about getting better at it?

UMMS - James Fodor - Peter Singer

Nick, James, and Peter Singer during Q&A

Around this central idea a new movement has emerged over the past few years known as Effective Altruism, which seeks to use the best evidence available in order to help the most people and do the most good with the limited resources that we have available. Associated with this movement are organisations such as GiveWell, which evaluates the relative effectiveness of different charities, and Giving What We Can, which encourages members to pledge to donate 10% or more of their income to effective poverty relief programs.

Peter-Singer--Adam-Ford-1I was happy to get a photo with Peter Singer on the day – we organised to do an interview, and for Peter to come and speak at the Effective Altruism Global conference later in 2015.
Here you can find number of videos I have taken at various events where Peter Singer has addressed Effective Altruism and associated philosophical angles.

New Book ‘The Point of View of the Universe – Sidgwick and Contemporary Ethics‘ – by Katarzyna de Lazari-Radek and Peter Singer

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My students often ask me if I think their parents did wrong to pay the $44,000 per year that it costs to send them to Princeton. I respond that paying that much for a place at an elite university is not justified unless it is seen as an investment in the future that will benefit not only one’s child, but others as well. An outstanding education provides students with the skills, qualifications, and understanding to do more for the world than would otherwise be the case. It is good for the world as a whole if there are more people with these qualities. Even if going to Princeton does no more than open doors to jobs with higher salaries, that, too, is a benefit that can be spread to others, as long as after graduating you remain firm in the resolve to contribute a percentage of that salary to organizations working for the poor, and spread this idea among your highly paid colleagues. The danger, of course, is that your colleagues will instead persuade you that you can’t possibly drive anything less expensive than a BMW and that you absolutely must live in an impressively large apartment in one of the most expensive parts of town.Peter Singer, The Life You Can Save: Acting Now to End World Poverty, London, 2009, pp. 138-139

 

Playlist of video interviews and talks by Peter Singer:

 

Science, Technology & the Future

 

Understanding the New Statistics

Geoff discusses statistics, confidence intervals, Bayesian approaches, meta-analysis, and problems with the use of ‘P’ values in significance testing.

Geoff Cumming v2.00_00_19_07.Still003Discussion points:
– Describe your background and involvement in statistics.
– How have orthodox statistics helped psychology (& science)? How has it harmed the science?
– What methods, models and tools do you commonly use in data analysis and why do you choose them?
– What is the dance of the p values? How do you cope with dancing p’s?
– What is meta-analysis & how is it done? How have meta-analysts coped with the bias in publishing data and results? What has the profession done about it?
– Confidence intervals help compared to p’s, by providing info about variation. Do they help enough? Why not credible intervals? Do you see a role for Bayesian statistics in day-to-day science?
– Where is statistical inference heading? Is there a next big thing and, if so, what is it?
– Does every student need to learn computer programming (“coding”) nowadays?

Interviewed by Kevin Korb and Adam Ford at Monash University Clayton.

Geoff’s YouTube Channel can be found here.
About the book:
Cumming, G. (2012). Understanding The New Statistics: Effect Sizes, Confidence Intervals, and Meta-Analysis. New York: Routledge

–    Explains estimation, with many examples.
–    Designed for any discipline that uses statistical significance testing.
–    For advanced undergraduate and graduate students, and researchers.
–    Comes with free ESCI software.
–    May be the first evidence-based statistics textbook.
–    Assumes only prior completion of any intro statistics course.
–    See the dance of the confidence intervals, and many other intriguing things.

The main message of the book is summarised in two short magazine articles, in The Conversation, and InPsych.
Here is an interview on ABC Radio.

Buy ‘Understanding the New Statistics’ from Amazon

his is the first book to introduce the new statistics – effect sizes, confidence intervals, and meta-analysis – in an accessible way. It is chock full of practical examples and tips on how to analyze and report research results using these techniques. The book is invaluable to readers interested in meeting the new APA Publication Manual guidelines by adopting the new statistics – which are more informative than null hypothesis significance testing, and becoming widely used in many disciplines.

Geoff Cumming - The New StatisticsAccompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book’s exercises use ESCI’s simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice.

The book’s pedagogical program, built on cognitive science principles, reinforces learning:

  • Boxes provide “evidence-based” advice on the most effective statistical techniques.
  • Numerous examples reinforce learning, and show that many disciplines are using the new statistics.
  • Graphs are tied in with ESCI to make important concepts vividly clear and memorable.
  • Opening overviews and end of chapter take-home messages summarize key points.
  • Exercises encourage exploration, deep understanding, and practical applications.

This highly accessible book is intended as the core text for any course that emphasizes the new statistics, or as a supplementary text for graduate and/or advanced undergraduate courses in statistics and research methods in departments of psychology, education, human development , nursing, and natural, social, and life sciences. Researchers and practitioners interested in understanding the new statistics, and future published research, will also appreciate this book. A basic familiarity with introductory statistics is assumed.

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Simulating for Computational Biology – Arun Konagurthu

Arun Konagurthu - Simulating for Computational Biology v2Arun Konagurthu is a Senior Lecturer at the Clayton School of Computer Science and Information Technology, Faculty of Information Technology, Monash University. Between 2011-2013, Arun was additionally a Larkins Fellow at this faculty.

Arun leads a small research group that researches mainly in computational biology and bioinformatics. His other research interests include data structures and algorithms, computational modeling and simulation, combinatorial optimization, and, since joining Monash in 2011, statistical learning using Minimum Message Length inference.

Points of discussion:
– What’s your overall research problem? If you solved it, how would things change?
– What is ‘stringology’ and how is it relevant to your research problem?
– Describe your use of simulation methods in bioinformatics. What problems do they overcome and how?
– Why do you prefer Bayesian statistics? What difference does it make?
– How do simulation and scoring work together? What kind of scores do you use?
– What’s been the impact of simulation on bioinformatics generally?
– What’s the future of sampling in data science? What’s coming around the corner?

#bayesian #artificialintelligence #datascience

 

 

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Arun Konagurthu Simulating for Computational Biology v1