PDF电子书：Gel-Free Proteomics

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3 ]/ m; V- H" l: y1 `Gel-Free Proteomics
! s/ \& ]% j, H! F6 \! K+ p* G, x; _1 ?+ iContents
' [: u1 X. f! Z# A) n: GPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v/ T" F  w) R" \9 _( g
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix1 e; |' d2 h5 J! ^6 e/ b3 V- z
1. Mass Spectrometry-Driven Proteomics: An Introduction . . . . . . . . . . . . . 1
( f  y% a$ |+ e& TKenny Helsens, Lennart Martens, Joël Vandekerckhove,* B2 R' P2 q# T& \: i# \  C
and Kris Gevaert
; f0 q) d& k" f$ D) U& t/ r' S, g2. Metabolic Labeling of Model Organisms Using Heavy Nitrogen (15N) . . . . . . 29
3 |; B: D3 m/ A" U! j- M; UJoost W. Gouw, Bastiaan B.J. Tops, and Jeroen Krijgsveld; r+ Z! j4 U, e2 S. ?: I! h
3. Trypsin-Catalyzed Oxygen-18 Labeling for Quantitative Proteomics . . . . . . . 432 B+ m$ J; o- o, k+ R
Wei-Jun Qian, Brianne O. Petritis, Carrie D. Nicora,0 b- l! U$ Q" r0 i( o1 V
and Richard D. Smith; q/ _4 o5 O: _9 e4 u$ H% C
4. ICPL Labeling Strategies for Proteome Research . . . . . . . . . . . . . . . . . 55
7 I3 b& ?. N) |  Q! a* M2 r3 j+ A& }Friedrich Lottspeich and Josef Kellermann
  S9 V9 _' G" i3 l5. Quantitative Proteome Analysis Using Isobaric Peptide Termini. h& ]% X0 G% w! @5 e. i
Labeling (IPTL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
: t7 Q4 l0 g1 K# _% y! J4 tMagnus Ø. Arntzen, Christian J. Koehler, Achim Treumann, and Bernd Thiede% Y* n! x) o6 u1 g8 v$ T
6. Complete Chemical Modification of Amine and Acid Functional Groups+ w! W' V4 X5 ~! x
of Peptides and Small Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . 77$ }' e0 F' A5 v2 L& I
Casey J. Krusemark, Brian L. Frey, Lloyd M. Smith, and Peter J. Belshaw: J: u' H& e' ^0 L
7. Production and Use of Stable Isotope-Labeled Proteins for Absolute
3 G4 B* l7 S: Z" s( \- SQuantitative Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 930 N- B- H0 T  m9 K
Dorothée Lebert, Alain Dupuis, Jérôme Garin, Christophe Bruley,
) ~1 _4 Z0 _6 D( t: U4 qand Virginie Brun  c$ \& ~( E. b2 |
8. Organelle Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
, I! U/ B2 z: Q' y0 O! h' oSophie Duclos and Michel Desjardins
' w$ G7 H+ [1 G; k9. Membrane Protein Digestion – Comparison of LPI HexaLane
! |2 `: d% S  F/ |& i6 Q/ k& f1 nwith Traditional Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
4 t+ E. L1 N. Z$ RPing Sui, Tasso Miliotis, Max Davidson, Roger Karlsson, and Anders Karlsson% k2 x. C! t4 |4 B" u" Y# ?  B
10. GeLCMS for In-Depth Protein Characterization and Advanced Analysis: Z. s4 s9 U3 t/ A
of Proteomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
7 t% |' \' g0 E& Y" a9 L* h" P- ]Alicia Lundby and Jesper V. Olsen
: ]/ _, m) F# @" Z4 G0 K" b11. Exploring New Proteome Space: Combining Lys-N Proteolytic Digestion
  s, H, H! D- kand Strong Cation Exchange (SCX) Separation in Peptide-Centric3 N- }* J6 ~, t5 B* s. e
MS-Driven Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
+ W( v, K! a* `# W4 `12. Quantitation of Newly Synthesized Proteins by Pulse Labeling9 P- y& w/ c9 t; \2 @1 X! w
with Azidohomoalanine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
/ C& ?( Y( ], y5 H) F; b9 QGertjan Kramer, Piotr T. Kasper, Luitzen de Jong, and Chris G. de Koster" q' v# r8 r8 V4 {
13. Analytical Strategies in Mass Spectrometry-Based Phosphoproteomics . . . . . . . 183
# S( R8 a) }( a9 V$ |- |Heidi Rosenqvist, Juanying Ye, and Ole N. Jensen
. s) S( A2 W+ c0 m# f- o14. A Protocol on the Use of Titanium Dioxide Chromatography
( L/ O, p& ~) E$ N1 Xfor Phosphoproteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
7 J( s+ K3 B: P% J; DMartijn W.H. Pinkse, Simone Lemeer, and Albert J.R. Heck0 E% T2 f* y. a( B( A
15. Positional Proteomics at the N-Terminus as a Means of Proteome Simplification . 229
$ L* ^% X- \8 cGemma R. Davidson, Stuart D. Armstrong, and Robert J. Beynon
3 i  b& ^& ]# w8 p7 |4 L16. N-Terminomics: A High-Content Screen for Protease Substrates
( P6 D6 r0 O: g6 \: P6 Uand Their Cleavage Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2432 f3 H. D5 |9 w% Z
John C. Timmer and Guy S. Salvesen
, N+ m9 X3 o: |1 y. u, j2 K4 ?17. Protease Specificity Profiling by Tandem Mass Spectrometry Using
% B3 d/ _1 d  Y0 T/ AProteome-Derived Peptide Libraries . . . . . . . . . . . . . . . . . . . . . . . . 257
. e; _8 x6 g6 Q9 a& S! dOliver Schilling, Ulrich auf dem Keller, and Christopher M. Overall
+ X; U$ M3 U- N18. Identification of Proteolytic Products and Natural Protein N-Termini
( F5 z! C! I% [! w: dby Terminal Amine Isotopic Labeling of Substrates (TAILS) . . . . . . . . . . . . 273: H  L: v) G9 v+ T% j
Alain Doucet, Oded Kleifeld, Jayachandran N. Kizhakkedathu,
; ^  A% E4 r/ `! G4 \! O4 R( wand Christopher M. Overall1 P1 E% X. z( U# Z2 i* S/ @- w
19. Lectins as Tools to Select for Glycosylated Proteins . . . . . . . . . . . . . . . . 289
/ t: c" K( l' I4 {Els J.M. Van Damme
+ O3 l) C4 V) Y* K2 C20. Strong Cation Exchange Chromatography for Analysis of Sialylated Glycopeptides 2991 S) v- ]( a2 V
Katharina Lohrig, Albert Sickmann, and Urs Lewandrowski
3 X3 `. J. A  p' l. J21. Titanium Dioxide Enrichment of Sialic Acid-Containing Glycopeptides . . . . . . 309
+ i5 X' G" s9 ~2 D1 y, ]+ V) WGiuseppe Palmisano, Sara E. Lendal, and Martin R. Larsen
- B1 H; T- G! M3 [) O! U% d22. Chemical De-O-glycosylation of Glycoproteins for Applications- n8 `7 w0 Z2 ?
in LC-Based Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323" ?* G% y2 D7 x5 A. z! j7 A
Franz-Georg Hanisch  H% y% g1 t& a5 h- _# l
23. Ubiquitination and Degradation of Proteins . . . . . . . . . . . . . . . . . . . . 335
" @; S7 m4 t: j5 x6 JYelena Kravtsova-Ivantsiv and Aaron Ciechanover
2 P. P+ S* L2 S0 u" R1 R# M24. Bioinformatics Challenges in Mass Spectrometry-Driven Proteomics . . . . . . . 359+ ~+ T( q+ g+ k, j& w6 h5 l* @
Lennart Martens6 n! L! f, {& m9 k  Y- A
25. A Case Study on the Comparison of Different Software Tools8 u$ a5 `0 s7 [+ ]5 c# E* z
for Automated Quantification of Peptides . . . . . . . . . . . . . . . . . . . . . 373$ \! l/ _" U2 ]- B
Niklaas Colaert, Joël Vandekerckhove, Lennart Martens,
8 h& b% u8 `4 J2 ~and Kris Gevaert
# t2 I5 D" z" ySubject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399
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