Mark Robinson
University of Hertfordshire
28 Papers
115 Citations
Mark Robinson is an academic researcher from University of Hertfordshire. The author has contributed to research in topics: Support vector machine & DNA binding site. The author has an hindex of 11, co-authored 28 publications. Previous affiliations of Mark Robinson include Benaroya Research Institute & Virginia Mason Medical Center.
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Papers
Reassessing the chronology of Biblical Edom: new excavations and 14C dates from Khirbat en-Nahas (Jordan)
Thomas E. Levy,Russell B. Adams,Mohammad Najjar,Andreas Hauptmann,James D. Anderson,Baruch Brandl,Mark Robinson,Thomas Higham +7 more
TL;DR: In this article, an international team of researchers show how high-precision radiocarbon dating is liberating us from chronological assumptions based on Biblical research and prove that complex societies existed in Edom long before the influence of Assyrian imperialism was felt in the region from the eighth to sixth centuries BC.
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Tetrapod limb and sarcopterygian fin regeneration share a core genetic programme.
Acacio F. Nogueira,Carinne M. Costa,Jamily Lorena,Rodrigo N. Moreira,Gabriela N. Frota-Lima,Carolina Furtado,Mark Robinson,Chris T. Amemiya,Chris T. Amemiya,Sylvain Darnet,Igor Schneider +10 more
TL;DR: It is shown that lungfishes, the sister group of tetrapod, regenerate their fins through morphological steps equivalent to those seen in salamanders, lending strong support for the hypothesis that tetrapods inherited a bona fide limb regeneration programme concomitant with the fin-to-limb transition.
Atypical RNAs in the coelacanth transcriptome
Anne Nitsche,Gero Doose,Hakim Tafer,Mark Robinson,Nil Ratan Saha,Marco Gerdol,Adriana Canapa,Steve Hoffmann,Chris T. Amemiya,Chris T. Amemiya,Peter F. Stadler +10 more
TL;DR: More than 8,000 lincRNAs with normal gene structure and several thousands of circularized and trans-spliced products are observed, showing that such atypical RNAs form a substantial contribution to the transcriptome.
21
Using real-valued meta classifiers to integrate binding site predictions
Yi Sun,Mark Robinson,Rod Adams,Paul H. Kaye,Alistair G. Rust,Neil Davey +5 more
- 27 Dec 2005
TL;DR: It is found that support vector machines outperform each of the original individual algorithms and the other classifiers employed in this work and have a better tradeoff between recall and precision.
Improving computational predictions of cis-regulatory binding sites.
Mark Robinson,Yi Sun,Rene te Boekhorst,Paul H. Kaye,Rod Adams,Neil Davey,Alistair G. Rust +6 more
- 01 Dec 2005
TL;DR: An approach for improving the accuracy of a selection of established prediction algorithms is presented and it is shown that species specific optimization of algorithmic parameters can, in some cases, significantly improve the accuracyof algorithmic predictions.