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A strategy for extracting and analyzing large-scale quantitative epistatic interaction data.
Collins SR, Schuldiner M, Krogan NJ, Weissman JS
Genome Biol
2006,
7
:R63
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PubMed Central articles that cite the above article:
1.
Backup without redundancy: genetic interactions reveal the cost of duplicate gene loss.
Ihmels J, Collins SR, Schuldiner M, Krogan NJ, Weissman JS
Mol Syst Biol
2007,
3
:86
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CCR4/NOT complex associates with the proteasome and regulates histone methylation.
Laribee RN, Shibata Y, Mersman DP, Collins SR, Kemmeren P, Roguev A, Weissman JS, Briggs SD, Krogan NJ, Strahl BD
Proc Natl Acad Sci U S A
2007 Apr 3,
104
:5836-41
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3.
Buffering of deoxyribonucleotide pool homeostasis by threonine metabolism.
Hartman JL
Proc Natl Acad Sci U S A
2007 Jul 10,
104
:11700-5
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4.
Identification of yeast proteins necessary for cell-surface function of a potassium channel.
Haass FA, Jonikas M, Walter P, Weissman JS, Jan YN, Jan LY, Schuldiner M
Proc Natl Acad Sci U S A
2007 Nov 13,
104
:18079-84
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5.
Functional maps of protein complexes from quantitative genetic interaction data.
Bandyopadhyay S, Kelley R, Krogan NJ, Ideker T
PLoS Comput Biol
2008 Apr,
4
:e1000065
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6.
eQED: an efficient method for interpreting eQTL associations using protein networks.
Suthram S, Beyer A, Karp RM, Eldar Y, Ideker T
Mol Syst Biol
2008,
4
:162
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7.
Interactions between stressful environment and gene deletions alleviate the expected average loss of fitness in yeast.
Jasnos L, Tomala K, Paczesniak D, Korona R
Genetics
2008 Apr,
178
:2105-11
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8.
From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions.
Ulitsky I, Shlomi T, Kupiec M, Shamir R
Mol Syst Biol
2008,
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:209
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9.
Predicting quantitative genetic interactions by means of sequential matrix approximation.
Järvinen AP, Hiissa J, Elo LL, Aittokallio T
PLoS One
2008,
3
:e3284
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10.
Cost-effective strategies for completing the interactome.
Schwartz AS, Yu J, Gardenour KR, Finley RL, Ideker T
Nat Methods
2009 Jan,
6
:55-61
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11.
Stringent mating-type-regulated auxotrophy increases the accuracy of systematic genetic interaction screens with Saccharomyces cerevisiae mutant arrays.
Singh I, Pass R, Togay SO, Rodgers JW, Hartman JL
Genetics
2009 Jan,
181
:289-300
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12.
A complex-based reconstruction of the Saccharomyces cerevisiae interactome.
Wang H, Kakaradov B, Collins SR, Karotki L, Fiedler D, Shales M, Shokat KM, Walther TC, Krogan NJ, Koller D
Mol Cell Proteomics
2009 Jun,
8
:1361-81
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13.
Evolution of phosphoregulation: comparison of phosphorylation patterns across yeast species.
Beltrao P, Trinidad JC, Fiedler D, Roguev A, Lim WA, Shokat KM, Burlingame AL, Krogan NJ
PLoS Biol
2009 Jun 16,
7
:e1000134
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14.
High-throughput, quantitative analyses of genetic interactions in E. coli.
Typas A, Nichols RJ, Siegele DA, Shales M, Collins SR, Lim B, Braberg H, Yamamoto N, Takeuchi R, Wanner BL, Mori H, Weissman JS, Krogan NJ, Gross CA
Nat Methods
2008 Sep,
5
:781-7
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15.
Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions.
St Onge RP, Mani R, Oh J, Proctor M, Fung E, Davis RW, Nislow C, Roth FP, Giaever G
Nat Genet
2007 Feb,
39
:199-206
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16.
A comprehensive framework of E2-RING E3 interactions of the human ubiquitin-proteasome system.
van Wijk SJ, de Vries SJ, Kemmeren P, Huang A, Boelens R, Bonvin AM, Timmers HT
Mol Syst Biol
2009,
5
:295
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17.
Conservation and rewiring of functional modules revealed by an epistasis map in fission yeast.
Roguev A, Bandyopadhyay S, Zofall M, Zhang K, Fischer T, Collins SR, Qu H, Shales M, Park HO, Hayles J, Hoe KL, Kim DU, Ideker T, Grewal SI, Weissman JS, Krogan NJ
Science
2008 Oct 17,
322
:405-10
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18.
Reverse engineering a signaling network using alternative inputs.
Tanaka H, Yi TM
PLoS One
2009,
4
:e7622
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