Author: McGowan, Simon J. ; Terrett, Jonathan ; Brown, Clive G. ; Adam, Paul J. ; Aldridge, Louise ; Allen, Jason C. ; Amess, Bob ; Andrews, Kristian A. ; Barnes, Martin ; Barnwell, David E. ; Berry, Joanne ; Bird, Helen ; Boyd, Robert S. ; Broughton, Marissa J. ; Brown, Alice ; Bruce, Jim A. ; Brusten, Luc M. J. ; Draper, Nicholas J. ; Elsmore, Beverley M. ; Freeman, Colin D. ; Giles, David M. ; Gong, Haiping ; Gormley, Darren ; Griffiths, Matthew R. ; Hawkes, Tim D. R. ; Haynes, Paul S. ; Heesom, Kate J. ; Herath, Athula ; Hollis, Katherine ; Hudsen, Lindsey J. ; Inman, Janet ; Jacobs, Merrill ; Jarman, Darren ; Kibria, Imran ; Kilgour, John J. ; Kinuthia, Samuel K. ; Lane, Kim E. ; Lees, Margaret L. ; Loader, Julie ; Longmore, Andrew ; McEwan, Michael ; Middleton, Alice ; Moore, Stephen ; Murray, Carol ; Murray, Helen M. ; Myatt, C. Paul ; Ng, Stanley S. ; O'Neil, Andrew ; Parekh, Raj B. ; Patel, Ashok ; Patel, Kaajal B. ; Patel, Sonal ; Patel, Thakor P. ; Philp, Robin J. ; Platt, Albert E. ; Poyser, Helen ; Prendergast, Cynthia ; Prime, Sally ; Redpath, Nicholas ; Reeves, Mike ; Robinson, Andrew W. ; Rohlff, Christian ; Rosenbaum, Jeffrey M. ; Schenker, Martin ; Scrivener, Elaine ; Shipston, Nigel ; Siddiq, Shaistah ; Southan, Christopher ; Spencer, Daniel I. R. ; Stamps, Alasdair ; Steffens, Marc A. ; Stevenson, David ; Sweetman, Gavin M. A. ; Taylor, Stephen ; Townsend, Reid ; Ventom, Andrew M. ; Waller, Martin N. H. ; Weresch, Celia ; Williams, Amanda M. ; Woolliscroft, Richard J. ; Yu, Xiaohong ; Lyall, Andrew
The identification of protein-coding genes is currently based on the merging of evidence and predictions from a variety of databases that may themselves contain inaccurate and partial information. A method was developed for mapping accurate interpretations of protein MS-MS data to the genome. This approach enables verification of genes, exons, transcripts, and variant transcripts, as well as the de novo discovery of novel protein-coding genes. Improvements in spectral interpretation algorithms, multiple separation techniques, subcellular fractionation, and novel bioinformatics approaches are described to characterize >14,000 naturally occurring human genes.