The Technology and Transition

The best summary of the history of information technologies is a graph that shows the calculations per second per $1,000 from 1900 to today. (Try Googling calculations per second per $1,000) What we see when we look at these figures is exponential growth.

Up take of the printing press took hundreds of years; uptake of the radio and TV took decades; uptake of the computer and mobile phones took years. The kitsch and yet astonishing comparison that is usually trotted out in conversations like this is that there is over 100 times more computing power in our smart phone than there was in the Apollo Space pozycjonowanie Program. You have made the decision to sell your company. Maybe it was because A major company in a related industry just acquired a direct competitor. It could be that one of the industry giants recently acquired one of your small but worthy competitors and has removed the risk component of a buyer’s decision. Your fire to compete at your top level is not burning as brightly as it once did.
These are all good reasons to set your business sale process in motion. A critical element here is time. Given this scenario, the more rapidly you can get your acquisition opportunity in front of the viable buyers, the better your chance for more favorable sale terms and conditions.
All systems go, right? But wait. We have a major proposal out to that Blue Chip account and when we get that deal our sale price will sky rocket. So we are just going to wait for that deal to close and then put our company up for sale.

Each time we reach the capacity of one technology, a new one appears that takes the technology to the next level. Vacuum tubes were replaced by transistors, which were replaced by chips, which will probably be replaced by 3 dimensional self-organising molecular circuits or perhaps even quantum computers. Busy executives, decision makers and other people taking advantage of computing in work and meaningful pursuits need all the quality information they can get. They turn to the web because it has amassed huge amounts of information in almost all areas of human activities. But what is information in the first place? Technically speaking, “information is stimuli that have meaning in some context for its receiver. When information is entered into and stored in a computer, it is generally referred to as data – information translated into a form that is more convenient to move or process. When information is packaged or used for understanding or doing something, it is known as knowledge – to an enterprise or an individual, the possession of information or the ability to quickly locate it.” For the purpose here, I think the term ‘information’ is the correct description of some of what is available on the web, rather than knowledge or wisdom.

The 6th IAPR International Conference on Pattern Recognition in Bioinformatics

The conference is now over – thanks for your attendance. The proceedings can be browsed or bought online from Springer.

 

We look forward to meeting you at PRIB2012 in Japan!

In modern biology, high-throughput measurement devices allow scientists to gather data at unprecedented rates. To make sense of this data, computational biologists and system biologists construct quantitative models, many of which depend on pattern recognition techniques. Their application is challenging due to the large volumes of data and background information, noisy measurements and target outputs, highly diverse data types etc. The Pattern Recognition in Bioinformatics conference series aims to bring together researchers, practitioners and students from around the world to present and discuss recent developments and applications of pattern recognition methods in current bioinformatics, computational biology and systems biology. Authors are invited to submit full papers in relevant research areas, which include but are not limited to canada pharmacy online:

  • Bio-sequence analysis
  • Gene and protein expression analysis
  • Biomarker discovery
  • Protein structure and interaction prediction
  • Motifs and signal detection
  • Metabolic modelling and analysis
  • Systems and synthetic biology
  • Pathway and network analysis
  • Immuno- and chemo-informatics
  • Evolution and phylogeny
  • Bio-imaging
  • Biological databases, integration and visualisation

Pattern recognition techniques of interest include:

  • Statistical, syntactic and structural pattern recognition
  • Datamining and data-based modeling
  • Evolutionary computation
  • Bayesian networks and graphical models
  • Neural networks and fuzzy systems

Publication

Accepted papers will be published in Springer’s Lecture Notes in Bioinformatics (LNBI).

Important dates

• Paper submission June 26, 2011
• Author notification July 25, 2011
• Camera-ready paper August 24, 2011
• Poster abstract submission October 2, 2011
• Registration October 12, 2011