John Horgan argues that the pure science has ended. Full Stop.

I don’t understand how one can call the end of pure science when we have huge gaps in basic knowledge such as the origin of universe and time, origin of life, origin of consciousness, artificial intelligence, dark matter and dark energy, etc.

I don’t believe in his viewpoint. The science is fully flourishing these days. It may be true that the pace of fundamental discoveries and inventions might have been slowed but saying that it has been stopped all together would not be wise.

There is still hope for aspiring Darwins and Einsteins. Don’t lose hope, time will come.

I don’t know if they are mutually incompatible, but Richard Dawkins certainly thinks so. See this for an excellent interview of his on the same topic.

PS: I am a (Atheist+Agnostic)/2

Suppose we have a MxN grid with each cell having a particular (random) number. Also suppose that you are an organism capable of moving one cell left/right/up/down and accessing the number on the cell you are presently standing on. Moving takes away X units of energy/time and accessing the number takes Y units/time. You are assigned the task to search for a particular number NUM in the grid using the least amount of energy/time. You are allowed to choose the location (middle/corner/random) where you want to start searching. What will be your search strategy?

Will you do a systematic search or a clumsy search? Well, this is what I want to find out. I want to find out which is the best search strategy when there is a random chance of hitting upon the goal. Maybe, someone ( me, perhaps! ) should apply genetic programming to evolve agents who do this and then analyze their strategy.

This problem can be very exciting and can have huge applications.

Dear All,

We are happy to release yet another issue of Jeev. The October issue of Jeevhas an eclectic array of articles. The table of contents for the latest issue is:

Articles

* The “Conscious” Bacterium by Prof. Subramony Mahadevan

* Evolvability: Is it a misnomer or the basis of life? by Paras Chopra

* Biological data mining: Integration of biology and data mining by Aparna Bajaj

* Digital Evolution by Paras Chopra

Columns

* Interview of Prof. Subramony Mahadevan by Paras Chopra

* Company Profile - Shantha Biotechnics: An Indigenous Biotech Company by Anshuman Mirani

* A Different Perspective by Aakanksha Gaur

Extras

* The Biology Quiz by Soumya Lipsa Rath

* The Biotechnology Quiz by Deepak Singla

Your valuable feedback is welcome.

Warm Regards,
On behalf of the Editorial Team
Paras Chopra
Managing Editor

You might be thinking what kind of a post on Entrepreneurship is doing on the blog Biohacking. Well, the fact is that for the last 2-3 weeks I am in pretty charged-up mood. The other week, I read BusinessWorld’s (India) issue and it featured India’s 331 billionaires. Of these a whopping 74 billionaires made their wealth in last 5 years. If they can do it, why can’t I?

Since my interests lie mainly in computational biology, I longed to start a company in the same field. I researched heavily on the internet and have come to following conclusions:

1. Most (75%) of the entrepreneurs are poorer than their corporate peers. [1]
2. There is no perfect age for starting up your own business. You must wait till you identify the right opportunity. Indeed, the average age of an entrepreneur is 37. [1]
3. Prefer not to create an opportunity (or a trend). It is too risky. Instead try to identify an opportunity and capitalize on it.
4. Entrepreneurship may not be as cool as it looks.

I was advised that when you think that you have the following five things in hand, you must start a startup, else wait patiently. The things include:

1. Business model (opportunity)
2. Market
3. Capital
4. Team
5. Intellectual Property (patents, etc.)

I think I will some day start my own company, till then I will enjoy learning from the success stories of the startups.

Reference:
[1] Entrepreneurship, Age, and Money - Is It Better To Start Young or Wait Until You Are Older?

Simple. Work harder.

Self-Organizing Maps is a form of machine learning technique which
employs unsupervised learning. It means that you don’t need to explicitly
tell the SOM about what to learn in the input data. It automatically learns
the patterns in input data and organizes the data into different groups.

I have developed a Python module for SOM. The SOM which I have written
is little different from traditional SOMs because it supports supervised
learning also. It means that when you provide it with a sample set of
inputs and corresponding outputs, it learns to map future unknown inputs
to correct outputs. The code for solving the XOR problem using an SOM
is included in the code.

To read more about SOMs, click to:

• AI-Junkie’s very
  simple tutorial
• Wikipedia’s
  entry on Self-Organizing Maps

Click here to download the source code.

What’s that? Well, ENTP means Extraverted iNtuitive Thinking Perceiving. I took this online personality test recommed by Jonathan Dugan. I am highlighting some of the basic features of an ENTP.

• Clever
• Visinory
• Entrepreneur
• Innovator
• Intutive
• Fluent conversationalists, mentally quick, and enjoy verbal sparring with others
• ENTPs are less interested in developing plans of actions or making decisions than they are in generating possibilities and ideas

In a nutshell, this site says that:

ENTP
risk taker, easy going, outgoing, social, open, rule breaker, thrill seeker, life of the party, comfortable in unfamiliar situations, appreciates strangeness, disorganized, adventurous, talented at presentation, aggressive, attention seeking, experience junky, insensitive, adaptable, not easily offended, messy, carefree, dangerous, fearless, careless, emotionally stable, spontaneous, improviser, always joking, player, wild and crazy, dominant, acts without thinking, not into organized religion, pro-weed legalization

favored careers:
dictator, computer consultant, international spy, tv producer, philosopher, comedian, music performer, it consultant, figher pilot, politician, diplomat, entertainer, game designer, bar owner, freelance writer, creative director, strategist, news anchor, professional skateboarder, airline pilot, comic book artist, college professor, private detective, mechanical engineer, lecturer, ambassador, astronomer, research scientist, judge, web developer, scholar, fbi agent, cia agent, electrical engineer, assassin

disfavored careers:
personal assistant, wedding planner, travel agent, secretary, interior decorator, clerical employee, government employee, social worker, pre school teacher, copy editor, child care worker, hospitality worker, occupational therapist, home maker

Resources:

1. http://www.typelogic.com/entp.html
2. http://www.personalitypage.com/ENTP.html

PS: It is amazing that all of the characteristics which are mentioned about an ENTP match exactly with my characteristics.

Do these things have anything in common? If you think no, then think again because the genius lies in connecting unconnected concepts in a meaningful manner. Robert Axelrod, a political scientist at the University of Michigan in Ann Arbor, US, has applied the Game Theory to cancer phenomena and found that the tumor cells get more benefits (in terms of their growth) if they cooperate. If this is proved true, it could have major implications in terms of potential cancer therapies.

I feel it is quite a genius to see connections between two seemingly distinct fields. There are so many fields in which we have narrowed down our thinking thus excluding potential solutions. Is anyone there to see the connections?

Anyhow, here is the original news on the cancer and game theory.

There is much hype (or truth? ) around the net that Perl is THE language for bioinformatics. Having already learnt and programmed in Python, I somehow feel that the claims made by any programming language are shallow. In my opinion, Python is the most elegant language and most easily applicable one. No matter what problem you need to solve, Python provides an instant solution.

But, as I said that it is generally believed that the bioinformatics problems should be solved in Perl, I decided to learn the language. My first impressions with the language:

1. It is extremely programmer unfriendly (cryptic) language.
2. Anything which can be done in Perl, can be done in Python with more slickness and efficiency.
3. I wonder how Perl programmers read their code? The language is so weird.
4. Python also has a module supporting Bioinformatics problems called BioPython.
5. Learning Perl is like remembering all prime numbers from 1-1000 (there is no pattern).

In a nutshell, DON’T learn Perl. Instead learn Python and get a high!