Xref: utzoo comp.ai.neural-nets:1080 sci.bio:2472 Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!ncar!boulder!eesnyder From: eesnyder@boulder.Colorado.EDU (Eric E. Snyder) Newsgroups: comp.ai.neural-nets,sci.bio Subject: Re: Neural Nets in Gene Recognition Message-ID: <13693@boulder.Colorado.EDU> Date: 9 Nov 89 15:32:07 GMT References: <13550@boulder.Colorado.EDU> Sender: news@boulder.Colorado.EDU Reply-To: eesnyder@boulder.Colorado.EDU (Eric E. Snyder) Organization: University of Colorado, Boulder Lines: 211 Thanks for the several replies providing references on the subject. Several more people requested that I forward the information I recieved on the subject. Our mailer bounced several of these replies so I'll just post it here (the comp.ai people have probably seen it before): ************************************************************************* From: ohsu-hcx!spackmank@cse.ogc.edu (Dr. Kent Spackman) Subject: connectionist protein structure The two articles I mentioned are: Holley, L.H.; Karplus, M. Protein structure prediction with a neural network. Proceeding of National Academy of Science, USA; 1989; 86: 152-156. Qian, Ning; Sejnowski, Terrence J. Predicting the secondary structure of globular proteins using neural network models. J Mol Biol; 1988; 202: 865-884. I have an article that will be published in the proceedings of the Symposium on Computer Applications in Medical Care, in Washington, D.C., in November, entitled: "Evaluation of Neural Network Performance by ROC analysis: Examples from the Biotechnology Domain". Authors are M.L. Meistrell and myself. Kent A. Spackman, MD PhD Biomedical Information Communication Center (BICC) Oregon Health Sciences University 3181 SW Sam Jackson Park Road Portland, OR 97201-3098 From: Lambert.Wixson@MAPS.CS.CMU.EDU Subject: DNA,RNA, etc. Holley and Karplus, Proceedings of the National Academy of Science 86, 152-156 (89). ---- From: mv10801@uc.msc.umn.edu Subject: Re: applications to DNA, RNA and proteins George Wilcox (mf12801@sc.msc.umn.edu) does work on predicting protein tertiary structure using large backprop nets. --Jonathan Marshall Center for Research in Learning, Perception, and Cognition 205 Elliott Hall, Univ. of Minnesota, Minneapolis, MN 55455 ---- >From munnari!cluster.cs.su.OZ.AU!ray@uunet.UU.NET Fri Sep 29 23:40:55 1989 Subject: applications to DNA, RNA and proteins Borman, Stu "Neural Network Applications In Chemistry Begin to Appear", C&E News, April 24 1989, pp 24-28. Thornton, Janet "The shape of things to come?" Nature, Vol. 335 (1st September 1988), pp 10-11. You probably know about the Qian and Sejnowski paper already. The Thornton "paper" is a fast overview with a sentence or two comparing Q&S's work with other work. Borman's C&E piece is fairly superficial, but it mentions some other people who have played with this stuff, including Bryngelson and Hopfield, Holley and Karplus (who apparantly have published in Proc. Nat. Acad. Sci., 86(1), 152 (1989)) and Liebman. The 1990 Spring Symposium at Stanford (March 27-29, 1990) will have a session on "Artificial Intelligence and Molecular Biology". The CFP lists Neural Networks (very broad-minded of them!), so it might be worth a look when it comes around. From: "Evan W. Steeg" Subject: NNets and macromolecules There is a fair amount of work on applying neural networks to questions involving DNA, RNA, and proteins. The two major types of application are: 1) Using neural networks to predict conformation (secondary structure and/or tertiary structure) of molecules from their sequence (primary structure). 2) Using nets to find regularities, patterns, etc. in the sequence itself, e.g. find coding regions, search for homologies between sequences, etc. The two areas are not disjoint -- one might look for alpha-helix "signals" in a protein sequence as part of a structure prediction method, for example. I did my M.Sc. on "Neural Network Algorithms for RNA Secondary Structure Prediction", basically using a modified Hopfield-Tank (Mean Field Theory) network to perform an energy minimization search for optimal structures. A technical report and journal paper will be out soon. I'm currently working on applications of nets to protein structure prediction. (Reference below). Qian and Sejnowski used a feed-forward net to predict local secondary structure of proteins. (Reference above). At least two other groups repeated and extended the Qian & Sejnowski experiments. One was Karplus et al (ref. above) and the other was Cotterill et al in Denmark. (Discussed in a poster at the Fourth International Symposium on Artificial Intelligence Systems, Trento, Italy Sept. 1988). Finally, a group in Minnesota used a supercomputer and back-prop to try to find regularities in the 2-d distance matrices (distances between alpha-carbon atoms in a protein structure). An interim report on this work was discussed at the IJCNN-88 (Wash. DC) conference. (Sorry, I don't recall the names, but the two researchers were at the Minnesota Supercomputer Center, I believe.) As for the numerous research efforts in finding signals and patterns in sequences, I don't have these references handy. But the work of Lapedes of Los Alamos comes to mind as an interesting bit of work. Refs: E.W. Steeg. Neural Network Algorithms for the Prediction of RNA Secondary Structure. M.Sc. Thesis, Computer Science Dept., University of Toronto, Toronto, Ontario, Canada, 1988. Evan W. Steeg (416) 978-7321 steeg@ai.toronto.edu (CSnet,UUCP,Bitnet) Dept of Computer Science steeg@ai.utoronto (other Bitnet) University of Toronto, steeg@ai.toronto.cdn (EAN X.400) Toronto, Canada M5S 1A4 {seismo,watmath}!ai.toronto.edu!steeg ----- From: pastor@PRC.Unisys.COM (Jon Pastor) Subject: Re: applications to DNA, RNA and proteins @article(nakata85a, Author="K. Nakata and M. Kanehisa and D. DeLisi", Title="Prediction of splice junctions in mRNA sequences", Journal="Nucleic Acids Research", Year="1985", Volume="13", Number="", Month="", Pages="5327--5340", Note="", Annote="") @article(stormo82a, Author="G.D. Stormo and T.D. Schneider and L.M. Gold ", Title="Characterization of translational initiation sites in E. coli", Journal="Nucleic Acids Research", Year="1982", Volume="10", Number="", Month="", Pages="2971--2996", Note="", Annote="") @article(stormo82b, Author="G.D. Stormo and T.D. Schneider and L.M. Gold and A. Ehrenfeucht", Title="Use of the `perceptron' algorithm to distinguish translational initiation sites in E. coli", Journal="Nucleic Acids Research", Year="1982", Volume="10", Number="", Month="", Pages="2997--3010", Note="", Annote="") In addition, there is going to be (I think) a paper by Alan Lapedes, from Los Alamos, in a forthcoming book published by the Santa Fe Institute; my group also has a paper in this book, which is how I know about Lapedes' submission. I am going to try to contact the editor to see if I can get a preprint; if so, I'll let you know. I didn't attend the meeting at which Lapedes presented his paper, but I'm told that he was looking for splice junctions. ---- From: ff%FRLRI61.BITNET@CUNYVM.CUNY.EDU (Francoise Fogelman) Subject: proteins We have done some work on the prediction of secondary structures of proteins. This was presented at a NATO meeting (Les Arcs, march 1989) and will be published in the proceedings. F. Fogelman LRI Bat 490 Universite de Paris Sud 91405 ORSAY cedex FRANCE Tel 33 1 69 41 63 69 e-mail: ff@lri.lri.fr ---- The book "Evolution, Learning and Cognition", the article "Learning to Predict the Secondary Structure of Globular Proteins" by N. Qian & T. J. Sejnowski.