标题: 【KNOWLEADGE】Gene Function Analysis [打印本页] 作者: linxingxing 时间: 2010-6-7 20:19 标题: 【KNOWLEADGE】Gene Function Analysis
With the advent of high-throughput technologies, the number of genes of interest has expanded and the traditional methods for gene function analysis cannot achieve the throughput necessary for large-scale exploration. In Gene Function Analysis, a select team of experts bring together a number of recently developed techniques for studying gene function. The volume begins with a variety of computational techniques, which provide an excellent point of departure for the cutting-edge experimental methods that follow. Written in the highly successful Methods in Molecular Biology™ series format, each chapter surveys its subject with readily reproducible laboratory protocols, a list of the necessary materials, and the popular Notes section, which contains tips for troubleshooting and avoiding known pitfalls.( p2 m/ Z/ T; N0 e% v" s6 w
# h, G8 U9 }" H* z: d* }0 f3 rComprehensive and timely, Gene Function Analysis offers researchers a clear guide and the important tools they need to further study the intricate human genome.( j" K2 k4 ]# b, |$ ~" G
1 w8 i9 E7 X- @8 }Content Level » Research 5 ?1 m7 y" L9 b( {% p8 `2 r3 h* a- d4 P7 Y) Y, N5 m
Related subjects » Bioinformatics - Biotechnology - Cell Biology - Human Genetics * [9 C& P( Q0 D
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Table of contentstableOfContents 2 Y( i" I L9 \: |7 q pMethods in Molecular Biology: Gene Function Analysis. \8 w" X. w$ e5 B' E, R
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Table of Contents5 d1 l8 H- j" _! `, G
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Computational Methods I ; B/ R( @0 E! e I2 [! I. c* }$ h/ X2 X& s) L
1 Gene function inference from gene expression of deletion mutants3 H% t: V# L6 C0 U; H |: o
Ghislain Bidaut/ a, J' J. d. ~" |3 L
# b) q0 j: | e- H8 C4 J) J2 Association analysis for large scale gene set data$ d3 u, J9 U/ Y- D# Q
Stefan Kirov, Bing Zhang, Jay Snoddy8 G) I y- |& X; T7 g6 t- k
9 R5 k' @8 b" r; P3 Estimating Gene Function with Least Squares Nonnegative Matrix 8 a" ?" c& x: Y$ l" T2 QFactorization/ r; T. ]7 t* }' Z6 ]
Guoli Wang and Michael F. Ochs 6 Z1 l1 U/ ]5 {6 T& p 6 ~5 d3 a4 M0 t1 [9 }7 W4 From Promoter Analysis to Transcriptional Regulatory Network ' P" e+ s: p. l3 s/ v, p0 E# o/ [Prediction Using PAINT6 b8 l7 b+ L! L% I G
Gregory E. Gonye, Praveen Chakravarthula, James S. Schwaber, - Q% U5 u6 O3 N& ]8 p" W7 pRajanikanth Vadigepalli# J1 E& b% U( R) b
4 U& j& f5 y# v9 D( C5 Prediction of Intrinsic Disorder and its Use in Functional Proteomics* }1 z9 W$ I. q+ Z; H
Vladimir N. Uversky, Predrag Radivojac, Lilia M. Iakoucheva, Zoran: r6 G# y) {4 U' `( A, L7 F9 H8 W+ x$ b
Obradovic, A. Keith Dunker% g# O. N! i. p/ T- k
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Computational Methods II# @9 y$ J+ \; t: q6 A
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6 Sybil: Methods and Software for Multiple Genome Comparison and `7 s3 g& t& z1 \& m9 [0 h
Visualization 0 [! r- s& z: D, ^& LJonathan Crabtree, Samuel V. Angiuoli, Jennifer R. Wortman, Owen White& k6 Y1 s8 Y w6 y7 V/ f F
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7 Estimating protein function using protein-protein relationships: ]3 s& w6 |( b! J( X- z2 r
Shailesh V. Date 4 K3 t- L) ]: D2 ~1 |, v" I 8 |+ L# D+ ]% r0 W3 T* p& y! d8 Bioinformatics tools for modeling transcription factor target genes 1 j# ]+ t% q- c. j$ q2 u( P. v$ Hand epigenetic changes ! W. n. k- M: bRamana V. Davuluri ( k2 t0 }1 ?* q8 P( ^ a$ b& |# [* m% E6 `
9 Mining Biomedical Data Using MetaMap Transfer (MMTx) and the Unified ! r8 W. n0 F; T' ~& t9 C5 lMedical Language System (UMLS) / N4 v4 D: {; r2 JJohn D. Osborne, Simon Lin, Lihua (Julie) Zhu, Warren A. Kibbe * ^) t2 Z8 T \+ ~0 R) p( c( i, W! \0 c1 [( A H" [
10 Statistical Methods for Identifying Differentially Expressed Gene & T+ r' K+ K- V* S3 E" RCombinations - \6 `, L4 N$ i; W3 nYen-Yi Ho, Leslie Cope, Marcel Dettling, Giovanni Parmigiani + j8 c/ }) [2 P% t2 c x: j! F0 @5 v+ B; Q9 I; ?* o ; B, E# a7 v; }2 _8 b( {4 ^Experimental Methods1 `; ^" k) \# y, f H0 t
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11 Gene Function Analysis using the chicken B-cell Line DT40% @+ ?1 [, g8 f5 H/ P# k4 B
Randolph B Caldwell, Petra Fiedler, Ulrike Schoetz and Jean-Marie + Q% \* e i# e2 q! rBuerstedde " h; r% d o+ c , d/ t h6 h2 }$ X12 Design and application of an shRNA-based gene replacement retrovirus.# C, T6 A9 h: j3 a( p
Rugang Zhang, Peter D. Adams and Xiaofen Ye' U: V: l% B( t* O
; Y5 I% z7 [% g. s/ d3 G9 W6 A g13 Construction of simple and efficient DNA vector-based short hairpin 5 a6 L' j) D1 G% N) N/ e! TRNA 9 H* R3 s( j2 A7 rexpression systems for specific gene silencing in mammalian cells: C+ ?% w5 k1 I; ?0 I4 m
Tsung-Lin Cheng a and Wen-Tsan Chang 0 z }' n3 O0 Z6 ~ . B7 z2 B) E& K( S2 n. b5 o; W) {14 Selection of recombinant antibodies from antibody gene libraries 3 b+ [! }5 c& X# Z; T/ f8 bMichael Hust, Stefan Dübel and Thomas Schirrmann) ?! W' J* R" b; T' n6 W
. I1 i) U. n! A9 w2 E9 A15 A bacterial/yeast merged two-hybrid system: protocol for yeast4 e: z+ O7 m2 R# T: {
screening with single or parallel baits.% ], ~4 ^2 F) o
Nadezhda Tikhmyanova, Eugene Izumchenko, Ilya G. Serebriiskii, Erica A.1 s4 e2 k3 K9 K) ^3 \
Golemis4 f" ] }5 d( r9 K6 X
% @3 @$ i' ~: U# {16 A bacterial/yeast merged two-hybrid system: protocol for bacterial# t: c9 M* A. @8 Q( W
screening' R3 o4 K; Q$ A% }
Ilya G. Serebriiskii, Nadia Milech, Erica A. Golemis + k! E2 z' A( q1 j" E1 ^ + r& s9 P% Q' C17 Engineering Cys2His2 Zinc Finger Domains using a Bacterial9 }. ]1 X6 O. z& f( J. b
Cell-Based Two-Hybrid Selection System + R' K/ T1 @; ~+ H3 k9 N" d/ n7 ZStacey Thibodeau-Beganny and J. Keith Joung作者: linxingxing 时间: 2010-6-7 20:26
Functional Analysis Program# w$ }( R% q& M. e+ d, E
Overview $ U# N. Y: B' f" i ^6 f
Research Objectives # R- `, y: { v( @* Q
Policies, Reports and Related Project Information 1 D) g' o% \. \7 q6 v, r
Funding Opportunities . A! Z8 Z* g7 RStaff c1 O4 F# U7 p& b% v! R! q2 o7 i" v9 N, v. h; G% |" x/ ?
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Functional Analysis Program Overview ( l" ^% E+ v9 ?2 g- }, I# M$ a% B" BCompletely sequencing an organism's genome is just the beginning of our understanding of that organism's biology. All of the genes still need to be identified; the function of those genes' expressed products (functional RNAs and proteins) must be elucidated; and the non-coding regulatory sequences need to be understood. The Functional Analysis of the Genome program manages and supports research that will lead to improved techniques and strategies for efficient identification and functional analysis of genes, coding regions and other functional elements of entire genomes on a high throughput basis.8 A, U2 Q6 `8 R4 a/ z! d/ d2 u$ e" i
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The main emphasis of this program is technology development. These technologies must be efficient, robust and have the potential to be applied in a large-scale yet cost-effective manner. The program also supports the large-scale application of high-throughput and efficient technologies on a limited basis, primarily in model organisms. (The application of these technologies to specific, highly focused biological or medical problems is not supported under this program). 5 t" f8 n9 H O6 C/ L: P8 }+ y- ?. f4 m8 J: o
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Functional Analysis Program Research Objectives: ( a; O: F5 A4 G+ N8 L
Identification and mapping of all functional elements (both coding and non-coding) in a genome.& F. l! M& }( k+ `9 w4 N
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; z& e& g* T+ S7 j* R/ L1 fGeneration of high-quality, full-length and representative cDNA libraries. ) c& ~! t3 a) e% L% T2 u 7 Q) Y8 Z' o/ [, d6 T8 O / \( p5 z! P1 c, P& ?/ d+ |3 BAnalysis of steady-state RNA and protein expression levels in a given cell type; of comparative levels of gene products in different cell types; and of temporal or induced changes in RNA and protein expression. ) n; a) z* B0 C/ I3 P8 N/ w8 G- ?+ F; ?' h
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Analysis of naturally occurring or induced mutations that alter RNA and/or protein expression.7 h9 b8 w7 x5 E2 u$ w* q
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Analysis of cellular localization of proteins and of protein-protein, or protein-nucleic acid, interactions.3 `- `. Z5 `! K3 @
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Comparative analysis of protein sequences. 1 m8 T! A" k n9 U L9 U! k, O" b2 T) e5 S
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Analysis of genome organization and its effect on cellular functions. 9 F& W4 `' [: \5 _" O" A% s' V2 Z
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Functional Analysis Program Policies, Reports and Related Program Information ! E8 t9 _8 `; L. X! a: j! o5 xWorkshop Reports " b: }8 I9 }, b9 h! c! e/ oWorkshop on the Comprehensive Extraction of Biological Information from Genomic Sequence July 23 - 24, 2002 # w0 M$ N5 `9 y7 c" L- J ) M. |' \4 X1 h. f. lNon-Mammalian Models Workshop [nih.gov] February 16-17, 1999 b* y) S6 `) Y5 d% Y# }" I; p% ~& G4 H% h1 R3 B/ L
Functional Analysis Workshop December 2-3, 1997# `" K" e) L- i6 t2 o( h& s
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Related Projects7 C& O, P: d, g
ENCODE (Encyclopedia of DNA Elements) 2 W K& r1 f" f5 T- mThe long-term goal of the ENCODE project is to identify all functional elements in the human genome sequence. For use in a pilot project, defined regions of the human genome - corresponding to 30Mb, roughly 1 percent - have been selected. These regions will serve as the foundation on which to test and evaluate the effectiveness and efficiency of a diverse set of methods and technologies for finding various functional elements in human DNA.8 t5 J7 ^& B- J1 ?$ ?) Q3 d
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Full-length cDNA Project (The Mammalian Gene Collection) [mgc.nci.nih.gov] % D$ h& K g+ z+ [+ F- r' R5 wThe goal of the Mammalian Gene Collection (MGC) project is to identify, sequence and make available to the research community, one representative, full-length (full open reading frame) clone for every human and mouse gene. The MGC website provides information about the confirmed, full ORF clones and cDNA libraries, and describes how to access the resources. The MGC is a trans-National Institutes of Health (NIH) initiative co-led by the National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI)., H3 z d7 q. x) h9 H* J) m5 v
6 s. t h) Y3 Q' y7 }4 @& g% [; x1 rModel Organisms for Biomedical Research [nih.gov]' g9 G8 c; {2 E K* k: U
Provides information and relevant links for trans-NIH model organism initiatives and their related funding opportunities. : ?/ r; N4 T9 C2 w7 Z$ o" `+ u) T+ L; U5 Z/ Q
Policies . S9 Y! |" D. L! s, PNHGRI Rapid Data Release Policy (January 2003) ! ~: \; Y7 n3 e 8 \2 b7 a( ]8 p* PNIH-DOE Guidelines for Access to Mapping and Sequencing Data and Material Resources (Spring 1998) * e# T% u3 w: _5 d% u$ l i, [, v- N% r% f3 ^& L! n/ H2 [
For additional information regarding data release for large-scale sequencing of model organism genomes, see: Guyer, M. Statement on the Rapid Release of Genomic DNA Sequence. Genome Research, 8(5): 413. 1998. [Full Text] + b0 Z" g5 W( T) @2 \5 S0 {- z7 V7 Y- g3 e! L
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e- | M% p8 dTop of page & Z5 J0 \5 t+ j/ D8 h# O4 R8 c) i + i% F2 B1 \: z) ?! b8 M0 OFunctional Analysis Program Funding Opportunities3 e8 J/ v+ P* ^; L& ^
Archival: PA-97-044: Technologies for Genomic Mapping, Sequencing and Analysis [Expired]4 J3 ^; S7 u' X% T# E" D
This announcement solicited investigator-initiated proposals to develop new technologies.6 \# k; X. w8 }5 t/ B$ Z& f
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Centers of Excellence in Genomic Science (CEGS) 6 D6 f, r9 J: \. E+ L1 L1 |- g/ o; t9 }4 S1 q
Expired Grant Solicitations0 l& ^8 L8 {7 @ J+ K' i* c/ `0 K
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Functional Analysis Program Staff ( K/ v2 U# F. U5 Z3 d9 K; qProgram Directors v( \- J5 N8 d; eElise Feingold, Ph.D., W) h2 Z, F3 e4 G
E-mail: feingole@exchange.nih.gov; b6 c' l/ G) u
5 ^5 y+ X! H! K. e* z( AGary Temple, Ph.D. , [1 {' `# I0 D# bE-mail: gtemple@mail.nih.gov! ~' ~. \- Z3 C& |
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Bettie Graham, Ph.D. }2 K) m8 A* @! H: ]% k# wE-mail: grahamb@nhgri.nih.gov $ H: n2 k# |+ _1 C9 J. ~8 p) N3 i' J/ O. k
Program Analysts ; P) m+ l; e1 {2 Y# M1 S! E( t. A , X' t# h9 r; o3 `! _Cristen Robinson$ \* B% O( j6 Z& z
E-mail: robinsoncr@mail.nih.gov $ ~9 G5 n" ?% W9 E# H1 [% U: ] 8 |, S- V: j: P1 Y; LAddress3 w0 {( V) S! ] [" p/ z$ G4 r
National Human Genome Research Institute . a4 p; C& N! t& v4 W. cNational Institutes of Health ) m* {) t$ }, R; ?, J5635 Fishers Lane% x. t1 y1 O) @. b
Suite 4076, MSC 93057 I1 C4 c/ B7 I* s
Bethesda, MD 20892-9305 3 z) v2 g7 s; R+ f: C* B# d4 E* A8 \/ ?
Phone: (301) 496-7531 % \& [ @) {! p3 V' i3 mFax: (301) 480-2770