View - ResearchGate
View - ResearchGate View - ResearchGate
Identifying Differentially Expressed Gene Combinations 19118. Cheng, Y. and Church, G. M. Biclustering of expression data. 93–103.19. Heckerman, D. (1995) A tutorial on learning with bayesian networks. Tech. rep.,Microsoft Research, Redmond, Washington. Revised June 96.20. Friedman, N. (2003) Probabilistic models for identifying regulation networks.Bioinformatics 19(Suppl 2), 1157.
- Page 348: 164 Osborne et al.amount of filteri
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- Page 356: 168 Osborne et al.Fig. 4. Input tes
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- Page 406: 194 Caldwell et al.for sequences th
- Page 410: 196 Caldwell et al.query because it
- Page 414: 198 Caldwell et al.Fig. 1. (A) Prot
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- Page 422: 202 Caldwell et al.5. Targeting scr
- Page 426: 204 Caldwell et al.will allow the s
- Page 430: 206 Caldwell et al.3.1.6. Plasmid P
- Page 434: 208 Caldwell et al.PCR amplify the
- Page 438: 210 Caldwell et al.8. Thawing cells
- Page 442: 212 Zhang et al.Going one step beyo
- Page 446: 214 Zhang et al.Fig. 2. Generation
Identifying Differentially Expressed Gene Combinations 19118. Cheng, Y. and Church, G. M. Biclustering of expression data. 93–103.19. Heckerman, D. (1995) A tutorial on learning with bayesian networks. Tech. rep.,Microsoft Research, Redmond, Washington. Revised June 96.20. Friedman, N. (2003) Probabilistic models for identifying regulation networks.Bioinformatics 19(Suppl 2), 1157.
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