Topics of Conference
The main topics include but will not be limited to (Excellent surveying works in these areas are welcome, too.)
Modelling the Cell
Study of Intelligence
Computing the Living System
Mathematics Meeting Anatomy
Hardware Meeting Biology
Revealing experimental techniques
Biologically Inspired Computation
Computing Learning or Behaviour
Architecture of Brain and Mind
Challenges in Biometrics
Computing Evolution and Origin of Disease
Molecular Biology Drug Discovery and Evolution
Psychology of human and machine
Computational Intelligence and Intelligent Systems
Presentational issues and social guarantees.
Interaction; Communication and Databases
Instincts, goal setting, emotions and machine intelligence
Can cybernetic principles and Shannon laws help Molecular Biology?
Forgotten technologies: resurrecting useful techniques lost in time
Macro and Micro Evolution: what impact has "species as the individual".
Linguistics and Genetics: parallels between languages and chemistry and what discoveries can these reveal.
Definition of Intelligence: requirement to manipulate the environment; creativity; common sense.
The C value enigma: new algorithms or tactics that may discover the putative function of DNA and of our cellular molecular machinery.
Complexity threshold in Genomics: measures to discover what is the complexity beyond which it becomes reasonable to apply Occam's Razor.
Modelling approaches: empirical science; reductionism and objections to reductionism; complex systems theory and emergence; taxonomic analysis; role of analogy in discoveries; chance discovery.
Cladistics: can we define mathematical existence and uniqueness; can we set any bounds on past and future evolution?
Context Databases: capturing context; feelings; hidden or intended meaning in databases
Socio-technical: design and usability challenges in the interaction between humans and their personal computational systems.
Bio Interaction: Interaction Technology between BioSystems and Machines.
Medical records and knowledge accumulation: where to place and how to ensure their integrity.
Research on Learning, and Predicting Social Behaviour or Culture
How do we learn most effectively? Which situations are learned best by means of simple mental exercises; or by playing pac -man; and which require immersion in realistic virtual reality games?
"Composability" problem: in a quickly put-together coalition each partner needs to guess the likely culture and behavior of the other partner, what is the best strategy for doing this?
Beyond Biostatistics. Can we reverse engineer and refine recognition algorithms from vast amounts of data using AI and "white-box" analysis?
Plausible new devices to improve human life: e.g. fusion of wearable sensors and natural language processing for personal use in pattern matching during daily activities.