David L Dowe

04-22-1998, 09:28 PM

Dear All,

Apologies for cross-postings.

In short,

if

you're interested in

MML or MDL or Akaike's Information Criterion or information theory

and you're interested in biology,

and you'd like to go to Hawaii in January 1999,

and you can get a paper ready by July 1998,

then

store this mail away and bookmark the site

http://www.cs.monash.edu.au/~dld/PSB99/PSB99.Info.CFPs.html

and read on.

================================================== =================

This is the Call For Papers for the 4th Pacific Symposium on BioComputing

(PSB99, 1999) conference track on "Information-theoretic approaches

to biology".

PSB-99 will be held from 4-9 January, 1999, in Mauni Lani on the

Big Island of Hawaii.

Track Organisers: David L. Dowe (dld@cs.monash.edu.au) and Klaus Prank.

WWW site: http://www.cs.monash.edu.au/~dld/PSB99/PSB99.Info.CFPs.html .

Specific technical area to be covered by this track:

Approaches to biological problems using notions of information or complexity,

including methods such as Algorithmic Probability, Minimum Message Length and

Minimum Description Length. Two possible applications are (e.g.) protein

folding and biological information processing.

Kolmogorov (1965) and Chaitin (1966) studied the notions of complexity and

randomness, with Solomonoff (1964), Wallace (1968) and Rissanen (1978) applying

these to problems of statistical and inferential learning (and ``data mining'')

and to prediction. The methods of Solomonoff, Wallace and Rissanen have

respectively come to be known as Algorithmic Probability (ALP), Minimum Message

Length (MML) and Minimum Description Length (MDL). All of these methods relate

to information theory, and can also be thought of in terms of Shannon's

information theory, and can also be thought of in terms of Boltzmann's

thermo-dynamic entropy.

An MDL/MML perspective has been suggested by a number of authors in the context

of approximating unknown functions with some parametric approximation scheme

(such as a neural network). The designated measure to optimize under this

scheme combines an estimate of the cost of misfit with an estimate of the cost

of describing the parametric approximation (Akaike 1973, Rissanen 1978,

Barron and Barron 1988, Wallace and Boulton, 1968).

This track invites all original papers of a biological nature which use

notions of information and/or information-theoretic complexity, with no strong

preference as to what specific nature. Such work has been done in problems of,

e.g., protein folding and DNA string alignment. As we shortly describe in some

detail, such work has also been done in the analysis of temporal dynamics in

biology such as neural spike trains and endocrine (hormonal) time series

analysis using the MDL principle in the context of neural networks and

context-free grammar complexity.

To elaborate on one of the relevant topics above, in the last three years

or so, there has been a major focus on the aspect of timing in biological

information processing ranging from fields such as neuroscience to

endocrinology. The latest work on information processing at the single-cell

level using computational as well as experimental approaches reveals previously

unimagined complexity and dynamism. Timing in biological information processing

on the single-cell level as well as on the systems level has been studied by

signal-processing and information-theoretic approaches in particular in the

field of neuroscience (see for an overview: Rieke et al. 1996). Using such

approaches to the understanding of temporal complexity in biological

information transfer, the maximum information rates and the precision of spike

timing to the understanding of temporal complexity in biological information

transfer, the maximum information rates and the precision of spike timing could

be revealed by computational methods (Mainen and Sejnowski, 1995; Gabbiani and

Koch 1996; Gabbiani et al., 1996).

The examples given above are examples of some possible biological application

domains. We invite and solicit papers in all areas of (computational) biology

which make use of ALP, MDL, MML and/or other notions of information and

information-theoretic complexity.

In problems of prediction, as well as using "yes"/"no" predictions, we would

encourage the authors to consider also using probabilistic prediction, where

the score assigned to a probabilistic prediction is given according to the

negative logarithm of the stated probability of the event.

Further comments re PSB-99 :

----------------------------

PSB99 will publish accepted full papers in an archival Proceedings. All

contributed papers will be rigorously peer-reviewed by at least three

referees. Each accepted full paper will be allocated up to 12 pages in the

conference Proceedings. The best papers will be selected for a 30-minute

oral presentation to the full assembled conference. Accepted poster

abstracts will be distributed at the conference separately from the

archival Proceedings. To be eligible for proceedings publication, each full

paper must be accompanied by a cover letter stating that it contains

original unpublished results not currently under consideration elsewhere.

See http://www.cgl.ucsf.edu/psb/cfp.html for more information.

IMPORTANT DATES:

Full paper submissions due: July 13, 1998

Poster abstracts due: August 22, 1998

Notification of paper acceptance: September 22, 1998

Camera-ready copy due: October 1, 1998

Conference: January 4 - 9, 1999

More information about the "Information-theoretic approaches to biology"

track, including a sample list of relevant papers is available on

the WWW at http://www.cs.monash.edu.au/~dld/PSB99/PSB99.Info.CFPs.html .

More information about PSB99 is available from

http://www.cgl.ucsf.edu/psb/cfp.html

For further information,

e-mail Dr. David Dowe, dld@cs.monash.edu.au

or e-mail Dr. Klaus Prank, ndxdpran@rrzn-serv.de .

This page was put together by

Dr. David Dowe,

School of Computer Science and Softw. Eng.,

Monash University, Clayton, Vic. 3168, Australia

e-mail: dld@cs.monash.edu.au

Fax: +61 3 9905-5146

http://www.csse.monash.edu.au/~dld/

and

Dr. Klaus Prank,

Abteilung Klinische Endokrinologie

Medizinische Hochschule Hannover

Carl-Neuberg-Str. 1

D-30623 Hannover

Germany

e-mail: ndxdpran@rrzn-serv.de

Tel.: +49 (511) 532-3827

Fax.: +49 (511) 532-3825

http://sun1.rrzn-user.uni-hannover.de/~ndxdpran/

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-------------------------------------------------------------------

Apologies for cross-postings.

In short,

if

you're interested in

MML or MDL or Akaike's Information Criterion or information theory

and you're interested in biology,

and you'd like to go to Hawaii in January 1999,

and you can get a paper ready by July 1998,

then

store this mail away and bookmark the site

http://www.cs.monash.edu.au/~dld/PSB99/PSB99.Info.CFPs.html

and read on.

================================================== =================

This is the Call For Papers for the 4th Pacific Symposium on BioComputing

(PSB99, 1999) conference track on "Information-theoretic approaches

to biology".

PSB-99 will be held from 4-9 January, 1999, in Mauni Lani on the

Big Island of Hawaii.

Track Organisers: David L. Dowe (dld@cs.monash.edu.au) and Klaus Prank.

WWW site: http://www.cs.monash.edu.au/~dld/PSB99/PSB99.Info.CFPs.html .

Specific technical area to be covered by this track:

Approaches to biological problems using notions of information or complexity,

including methods such as Algorithmic Probability, Minimum Message Length and

Minimum Description Length. Two possible applications are (e.g.) protein

folding and biological information processing.

Kolmogorov (1965) and Chaitin (1966) studied the notions of complexity and

randomness, with Solomonoff (1964), Wallace (1968) and Rissanen (1978) applying

these to problems of statistical and inferential learning (and ``data mining'')

and to prediction. The methods of Solomonoff, Wallace and Rissanen have

respectively come to be known as Algorithmic Probability (ALP), Minimum Message

Length (MML) and Minimum Description Length (MDL). All of these methods relate

to information theory, and can also be thought of in terms of Shannon's

information theory, and can also be thought of in terms of Boltzmann's

thermo-dynamic entropy.

An MDL/MML perspective has been suggested by a number of authors in the context

of approximating unknown functions with some parametric approximation scheme

(such as a neural network). The designated measure to optimize under this

scheme combines an estimate of the cost of misfit with an estimate of the cost

of describing the parametric approximation (Akaike 1973, Rissanen 1978,

Barron and Barron 1988, Wallace and Boulton, 1968).

This track invites all original papers of a biological nature which use

notions of information and/or information-theoretic complexity, with no strong

preference as to what specific nature. Such work has been done in problems of,

e.g., protein folding and DNA string alignment. As we shortly describe in some

detail, such work has also been done in the analysis of temporal dynamics in

biology such as neural spike trains and endocrine (hormonal) time series

analysis using the MDL principle in the context of neural networks and

context-free grammar complexity.

To elaborate on one of the relevant topics above, in the last three years

or so, there has been a major focus on the aspect of timing in biological

information processing ranging from fields such as neuroscience to

endocrinology. The latest work on information processing at the single-cell

level using computational as well as experimental approaches reveals previously

unimagined complexity and dynamism. Timing in biological information processing

on the single-cell level as well as on the systems level has been studied by

signal-processing and information-theoretic approaches in particular in the

field of neuroscience (see for an overview: Rieke et al. 1996). Using such

approaches to the understanding of temporal complexity in biological

information transfer, the maximum information rates and the precision of spike

timing to the understanding of temporal complexity in biological information

transfer, the maximum information rates and the precision of spike timing could

be revealed by computational methods (Mainen and Sejnowski, 1995; Gabbiani and

Koch 1996; Gabbiani et al., 1996).

The examples given above are examples of some possible biological application

domains. We invite and solicit papers in all areas of (computational) biology

which make use of ALP, MDL, MML and/or other notions of information and

information-theoretic complexity.

In problems of prediction, as well as using "yes"/"no" predictions, we would

encourage the authors to consider also using probabilistic prediction, where

the score assigned to a probabilistic prediction is given according to the

negative logarithm of the stated probability of the event.

Further comments re PSB-99 :

----------------------------

PSB99 will publish accepted full papers in an archival Proceedings. All

contributed papers will be rigorously peer-reviewed by at least three

referees. Each accepted full paper will be allocated up to 12 pages in the

conference Proceedings. The best papers will be selected for a 30-minute

oral presentation to the full assembled conference. Accepted poster

abstracts will be distributed at the conference separately from the

archival Proceedings. To be eligible for proceedings publication, each full

paper must be accompanied by a cover letter stating that it contains

original unpublished results not currently under consideration elsewhere.

See http://www.cgl.ucsf.edu/psb/cfp.html for more information.

IMPORTANT DATES:

Full paper submissions due: July 13, 1998

Poster abstracts due: August 22, 1998

Notification of paper acceptance: September 22, 1998

Camera-ready copy due: October 1, 1998

Conference: January 4 - 9, 1999

More information about the "Information-theoretic approaches to biology"

track, including a sample list of relevant papers is available on

the WWW at http://www.cs.monash.edu.au/~dld/PSB99/PSB99.Info.CFPs.html .

More information about PSB99 is available from

http://www.cgl.ucsf.edu/psb/cfp.html

For further information,

e-mail Dr. David Dowe, dld@cs.monash.edu.au

or e-mail Dr. Klaus Prank, ndxdpran@rrzn-serv.de .

This page was put together by

Dr. David Dowe,

School of Computer Science and Softw. Eng.,

Monash University, Clayton, Vic. 3168, Australia

e-mail: dld@cs.monash.edu.au

Fax: +61 3 9905-5146

http://www.csse.monash.edu.au/~dld/

and

Dr. Klaus Prank,

Abteilung Klinische Endokrinologie

Medizinische Hochschule Hannover

Carl-Neuberg-Str. 1

D-30623 Hannover

Germany

e-mail: ndxdpran@rrzn-serv.de

Tel.: +49 (511) 532-3827

Fax.: +49 (511) 532-3825

http://sun1.rrzn-user.uni-hannover.de/~ndxdpran/

-------------------------------------------------------------------

To unsubscribe send UNSUBSCRIBE BIOMCH-L to LISTSERV@nic.surfnet.nl

For information and archives: http://www.bme.ccf.org/isb/biomch-l

-------------------------------------------------------------------