Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Transcription factor binding predicts histone modifications in human cell lines

    Benveniste, D., Sonntag, H-J., Sanguinetti, G. & Sproul, D., 16 Sep 2014, In : Proceedings of the National Academy of Sciences. 111, 37, p. 13367-72 6 p.

    Research output: Contribution to journalArticle

  2. Transcription rate strongly affects splicing fidelity and cotranscriptionality in budding yeast

    Aslanzadeh, V., Huang, Y., Sanguinetti, G. & Beggs, J., 2018, In : Genome Research. 12 p.

    Research output: Contribution to journalArticle

  3. Transcriptional Analysis of Gli3 Mutants Identifies Wnt Target Genes in the Developing Hippocampus

    Hasenpusch-Theil, K., Magnani, D., Amaniti, E-M., Han, L., Armstrong, D. & Theil, T., Dec 2012, In : Cerebral Cortex. 22, 12, p. 2878-2893 16 p.

    Research output: Contribution to journalArticle

  4. Transformation Equivariant Boltzmann Machines

    Kivinen, J. J. & Williams, C. K. I., 2011, Artificial Neural Networks and Machine Learning - ICANN 2011: 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Honkela, T., Duch, W., Girolami, M. & Kaski, S. (eds.). Springer-Verlag GmbH, p. 1-9 9 p. (Lecture Notes in Computer Science; vol. 6791).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. Transition of Escherichia coli from Aerobic to Micro-aerobic Conditions Involves Fast and Slow Reacting Regulatory Components

    Partridge, J. D., Sanguinetti, G., Dibden, D. P., Roberts, R. E., Poole, R. K. & Green, J., Apr 2007, In : Journal of Biological Chemistry. 282, 15, p. 11230-11237 8 p.

    Research output: Contribution to journalArticle

  6. Transmission of population-coded information

    Renart, A. & van Rossum, M. C. W., Feb 2012, In : Neural Computation. 24, 2, p. 391-407 17 p.

    Research output: Contribution to journalArticle

  7. Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3

    Huynh-Thu, V. A. & Sanguinetti, G., 2019, Gene Regulatory Networks: Methods and Protocols. Sanguinetti, G. & Huynh-Thu, V. A. (eds.). New York, NY: Springer New York LLC, p. 217-233 17 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  8. Tree-structured belief networks as models of images

    Feng, X. & Williams, C. K. I., 1 Jan 1999, Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470). IET, p. 31-36 5 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  9. Trends and challenges in Computational RNA biology

    Selega, A. & Sanguinetti, G., 7 Dec 2016, In : Genome Biology. 17, 253, p. 1-4 4 p.

    Research output: Contribution to journalMeeting abstract

  10. Truncated covariance matrices and Toeplitz methods in Gaussian processes

    Storkey, AJ., 1999, Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470) (Volume:1 ) . EDISON: INST ELECTRICAL ENGINEERS INSPEC INC, p. 55-60 6 p. (IEE CONFERENCE PUBLICATIONS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution