Filters








14,260 Hits in 8.8 sec

The role of pattern recognition in creative problem solving: A case study in search of new mathematics for biology

Felix T. Hong
2013 Progress in Biophysics and Molecular Biology  
Attempts to build mathematical theories for biology in the past century was met with modest and sporadic successes, and only in simple systems.  ...  In this article, a qualitative model of humans' high creativity is presented as a starting point to consider whether the gap between soft and hard sciences is bridgeable.  ...  The author also takes this opportunity to remember a very special individual: Michael Conrad of Wayne State University.  ... 
doi:10.1016/j.pbiomolbio.2013.03.017 pmid:23597605 fatcat:y6cnc2scnjcsbh6m3qz72a4kzu

Machine learning applications in bioinformatics

Jirí Kléma
2012 Conference on Theory and Practice of Information Technologies  
Similarly to the domain of pattern mining, recent efforts in the field of molecular classification aim to employ background knowledge.  ...  Nevertheless, molecular classifiers based solely on gene expression in most cases cannot be considered useful decision-making tools or decision-supporting tools.  ... 
dblp:conf/itat/Klema12 fatcat:olxmaiwpgjce3bwbuw45napamy

Logic-Based Machine Learning [chapter]

Stephen Muggleton, Flaviu Marginean
2000 Logic-Based Artificial Intelligence  
Acknowledgements Thanks are due to the funders and researchers who helped develop the technology and applications of ILP on the Esprit projects ECOLES (1989)(1990)(1991)(1992), ILP I (1992), ILPnet (1992  ...  In our investigation it was found that the ability to make use of background knowledge from molecular biology, together with the ability to describe structural relations boosted the predictivity for a  ...  In Golem was applied to one of the hardest open problems in molecular biology.  ... 
doi:10.1007/978-1-4615-1567-8_14 fatcat:n4ql555nlvg5pcjtgfae5wetxu

Introduction

Jude Shavlik, Lawrence Hunter, David Searls
1995 Machine Learning  
In fact, arguably the machine learning application with the largest impact on molecular biology is Uberbacher and Mural's (1991) GRAIL system, which uses neural networks to find genes in DNA sequences  ...  The field of molecular biology is rich in problems that seem almost tailor-made for machine learning approaches.  ...  They also discuss the general problem of using domain knowledge to improve the input representation used in a machine learning task.  ... 
doi:10.1007/bf00993376 fatcat:lqar2iebbvhsnorwjvix2n6bsm

Learning Constrained Edit State Machines

Laurent Boyer, Olivier Gandrillon, Amaury Habrard, Mathilde Pellerin, Marc Sebban
2009 2009 21st IEEE International Conference on Tools with Artificial Intelligence  
Experimental results are provided on a task in molecular biology, aiming to detect transcription factor binding sites.  ...  Although the use of such models has lead to significant improvements of edit distance-based classification tasks, a new challenge has appeared on the horizon: How integrating background knowledge during  ...  In order to improve the expressiveness of pair-HMMs, we aim to incorporate knowledge during the learning process in the form of constraints.  ... 
doi:10.1109/ictai.2009.27 dblp:conf/ictai/BoyerGHPS09 fatcat:7fcuf4hfvrebxhmmh66ui53f5a

WIBL: Workbench for Integrative Biological Learning

Victor Lesk, Jan Taubert, Chris Rawlings, Stuart Dunbar, Stephen Muggleton
2011 Journal of Integrative Bioinformatics  
WIBL combines data integration, visualisation and modelling in a single portal-based workbench providing a comprehensive solution for interdisciplinary systems biology projects.  ...  The construction of integrated datasets from potentially hundreds of sources with bespoke formats, and their subsequent visualization and analysis, is a recurring challenge in systems biology.  ...  The model uses KEGG data on metabolism to learn from observations in a pilot study of liver toxicity induced by phenobarbital in rat which is being used to develop a model of the differences between rodent  ... 
doi:10.2390/biecoll-jib-2011-156 pmid:21705808 fatcat:miaxrlorjbhqrgms6xalwoigr4

WIBL: Workbench for Integrative Biological Learning

Victor Lesk, Jan Taubert, Chris Rawlings, Stuart Dunbar, Stephen Muggleton
2011 Journal of Integrative Bioinformatics  
WIBL combines data integration, visualisation and modelling in a single portalbased workbench providing a comprehensive solution for interdisciplinary systems biology projects.  ...  SummaryThe construction of integrated datasets from potentially hundreds of sources with bespoke formats, and their subsequent visualization and analysis, is a recurring challenge in systems biology.  ...  The model uses KEGG data on metabolism to learn from observations in a pilot study of liver toxicity induced by phenobarbital in rat which is being used to develop a model of the differences between rodent  ... 
doi:10.1515/jib-2011-156 fatcat:gidd676o6jemflabl3h3xkr524

Digital Learning Material for Model Building in Molecular Biology

Tinri Aegerter-Wilmsen, Fred Janssen, Rob Hartog, Ton Bisseling
2005 Journal of Science Education and Technology  
In order to provide students the opportunity to improve their model building skills, we decided to develop a number of digital cases about developmental biology.  ...  However, in molecular biology curricula little attention is generally being paid to the development of this skill.  ...  We also thank the other scientists and the students who participated in this study.  ... 
doi:10.1007/s10956-005-2740-3 fatcat:2xspchn6c5gvxhpdqx22q5tknu

Applications of machine learning and rule induction

Pat Langley, Herbert A. Simon
1995 Communications of the ACM  
We consider rule induction in greater detail and review some of its recent applications, in each case stating the problem, how rule induction was used, and the status of the resulting expert system.  ...  An important area of application for machine learning is in automating the acquisition of knowledge bases required for expert systems.  ...  This work was funded in part by Grants N00014-94-1-0505 and N00014-94-1-0746 from the Office of Naval Research and the Advanced Research Projects Agency to the Institute for the Study of Learning and Expertise  ... 
doi:10.1145/219717.219768 fatcat:5gccbtwejbayzgfpv6t643odoq

A Systems Biology Approach to Learning Autophagy

Daniel J. Klionsky, Anuj Kumar
2006 Autophagy  
data set can be used to define the pathway in full-the information from multiple complementary studies must be integrated in order to recapitulate our present understanding of the pathways mediating autophagy  ...  As the data sets used in these class lessons are largely genomic and complementary in content, students will also understand first-hand the advantage of an integrative or systems biology study: No single  ...  ACKNOWLEDGEMENTS We would like to thank the U-M Life Sciences Learning Community (supported by a National Science Foundation Director's Award for Distinguished Teaching Scholars to D.J.  ... 
doi:10.4161/auto.2227 pmid:16874048 fatcat:ecrho65tszgxbgzfuwxy52qoa4

Recursive Feature Generation for Knowledge-based Learning [article]

Lior Friedman, Shaul Markovitch
2018 arXiv   pre-print
In this work, we present a novel algorithm for injecting external knowledge into induction algorithms using feature generation.  ...  When humans perform inductive learning, they often enhance the process with background knowledge.  ...  In this work, we present a novel algorithm that uses a similar approach for enhancing inductive learning with background knowledge through feature generation.  ... 
arXiv:1802.00050v1 fatcat:kjdpig26lfbohcsiazpblvkisi

Inductive Logic Programming: Issues, results and the challenge of Learning Language in Logic

Stephen Muggleton
1999 Artificial Intelligence  
This has allowed successful applications of ILP in areas such as molecular biology and natural language which both have rich sources of background knowledge and both benefit from the use of an expressive  ...  Logic programs are used as a single representation for examples, background knowledge and hypotheses.  ...  Acknowledgements The author would like to thank the following people who collaborated on research described in this paper: Mike Sternberg, Steve Pulman, Donald Michie, David Haussler, Ross King, David  ... 
doi:10.1016/s0004-3702(99)00067-3 fatcat:6fbihina7zba3neogm7knq45qe

Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology [chapter]

Oghenejokpeme I. Orhobor, Joseph French, Larisa N. Soldatova, Ross D. King
2020 Lecture Notes in Computer Science  
Here we demonstrate the use of relational learning to generate new data descriptors in such semantically complex background knowledge.  ...  The key to success in machine learning is the use of effective data representations.  ...  We hypothesized that we could improve both ML model explainability, and predictive accuracy, by including additional background knowledge in the learning process using a hybrid RL approach.  ... 
doi:10.1007/978-3-030-61527-7_25 fatcat:57l4nemeqrdbrc6av7fl2pdlxq

Teaching the bioinformatics of signaling networks: an integrated approach to facilitate multi-disciplinary learning

T. Korcsmaros, Z. A. Dunai, T. Vellai, P. Csermely
2013 Briefings in Bioinformatics  
Here, we present an outline of a university bioinformatics course with four sample practices to demonstrate how signaling network studies can integrate biochemistry, genetics, cell biology and network  ...  bioinformation can become obsolete in a few years.  ...  The structure of the presented course was based on a full-semester course of Eszter Ari and T.K. We thank the technical help of Janos Kubisch in the preparation of the manuscript.  ... 
doi:10.1093/bib/bbt024 pmid:23640570 fatcat:juk4nabsbrfsfgbulp2wr2mlhi

Learning in Clausal Logic: A Perspective on Inductive Logic Programming [chapter]

Peter Flach, Nada Lavrač
2002 Lecture Notes in Computer Science  
Inductive logic programming is a form of machine learning from examples which employs the representation formalism of clausal logic.  ...  , are still in use today.  ...  Part of the material in Sections 2-4 is based on a tutorial given by the first author at the First International Conference on Computational Logic (CL-2000).  ... 
doi:10.1007/3-540-45628-7_17 fatcat:i24bt6wv65crjjfybhcm7uwda4
« Previous Showing results 1 — 15 out of 14,260 results