【KNOWLEADGE】Gene Function Analysis

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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.$ p6 y2 G! W: r" H  p0 @
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Comprehensive and timely, Gene Function Analysis offers researchers a clear guide and the important tools they need to further study the intricate human genome.
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; d* Q4 B9 H7 |$ `8 X' ^Content Level » Research - ^+ z" P$ X; J8 H) ?( P. ]3 U  b# \
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Related subjects » Bioinformatics - Biotechnology - Cell Biology - Human Genetics , L* C4 w6 o8 ]  z
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Table of contentstableOfContents
; o. ^$ c7 |6 z' K, jMethods in Molecular Biology: Gene Function Analysis5 d; }7 g$ p3 C% |; C  F, C
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Table of Contents
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Computational Methods I( [6 w' P4 o- K9 e" m# M) T

4 n# ^% a2 m* b( v+ `* i4 y, N- _- w1 Gene function inference from gene expression of deletion mutants; b6 O$ h; R$ f) a( L* Z' B
Ghislain Bidaut0 \/ X, q1 w$ Q: k5 }

- r4 Z" O' \+ D+ [5 f- K2 Association analysis for large scale gene set data, y' m) J/ \/ a* F) r( y
Stefan Kirov, Bing Zhang, Jay Snoddy9 J* U, L# Y+ g& |

+ j) i: h( q- f1 ?/ w0 C3 Estimating Gene Function with Least Squares Nonnegative Matrix0 d6 W7 L, h3 B2 O
Factorization* Z+ s, _9 T" @9 N+ c8 V+ e
Guoli Wang and Michael F. Ochs
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4 From Promoter Analysis to Transcriptional Regulatory Network
+ k' Y* m  g' S5 PPrediction Using PAINT
& J, A0 T" ^! W* B( YGregory E. Gonye, Praveen Chakravarthula, James S. Schwaber,5 m( p( G0 V& n) R" k1 z) y0 u
Rajanikanth Vadigepalli
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7 j  @/ w. K; r: r4 X5 Prediction of Intrinsic Disorder and its Use in Functional Proteomics
: D6 r! B4 v8 C4 AVladimir N. Uversky, Predrag Radivojac, Lilia M. Iakoucheva, Zoran
7 ?% T8 k* z6 `8 l- T- B3 t# JObradovic, A. Keith Dunker+ n& H' ~- O: Z- }, @- d
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Computational Methods II
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6 Sybil: Methods and Software for Multiple Genome Comparison and
# Y7 L6 Q# p5 N2 X! BVisualization+ G6 q$ v( i5 o. u2 [& ]2 s
Jonathan Crabtree, Samuel V. Angiuoli, Jennifer R. Wortman, Owen White
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: e  ?4 S$ `4 B+ @4 m; {. P5 `7 Estimating protein function using protein-protein relationships% \' p" [& u& ~9 P! r
Shailesh V. Date
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% {2 _7 W: _% f8 J9 w6 J) p6 a3 |8 Bioinformatics tools for modeling transcription factor target genes
) v/ J. t9 H5 v0 E( W9 l4 u/ Rand epigenetic changes
1 ]( b' o) P" Z8 qRamana V. Davuluri  T( h: K2 L7 B* l7 e+ }

  f+ Y; c4 }9 k9 Mining Biomedical Data Using MetaMap Transfer (MMTx) and the Unified8 E0 P- e4 Y- Q# T9 \/ `; g& ^
Medical Language System (UMLS), q5 R1 x! m5 j, r% k/ j
John D. Osborne, Simon Lin, Lihua (Julie) Zhu, Warren A. Kibbe" E! |$ O. y& M# i/ f

; S! [: i  [$ E. {7 X10 Statistical Methods for Identifying Differentially Expressed Gene/ {/ \* f; {$ K* y% j8 t
Combinations
2 N+ ^5 `" Y, c( u* }Yen-Yi Ho, Leslie Cope, Marcel Dettling, Giovanni Parmigiani
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& r7 X3 n4 P3 p4 k9 MExperimental Methods, u: j# @# Z7 w" z" F" Q

2 P( P, l5 S% ?! n  V3 S7 J0 V11 Gene Function Analysis using the chicken B-cell Line DT40
) L. c2 X* \- s- N' `Randolph B Caldwell, Petra Fiedler, Ulrike Schoetz and Jean-Marie5 f6 X! @: L) `7 B
Buerstedde
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12 Design and application of an shRNA-based gene replacement retrovirus.( A$ i' h' X5 [* S
Rugang Zhang, Peter D. Adams and Xiaofen Ye& m  Y: z! ?' C

2 |* s. n) A% ]6 D13 Construction of simple and efficient DNA vector-based short hairpin
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expression systems for specific gene silencing in mammalian cells
' z" ~! l- ~4 l. R3 }! nTsung-Lin Cheng a and Wen-Tsan Chang
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14 Selection of recombinant antibodies from antibody gene libraries( `8 g5 w- ]8 W; ~/ @
Michael Hust, Stefan Dübel and Thomas Schirrmann4 ~' A; q* w6 V# v. @) i1 p. x

; k6 e7 ^7 I7 m. r. w% C+ f2 m15 A bacterial/yeast merged two-hybrid system: protocol for yeast
& F, u& l8 d" P8 h/ Z/ R" gscreening with single or parallel baits.# ^) y/ o4 P  p- W
Nadezhda Tikhmyanova, Eugene Izumchenko, Ilya G. Serebriiskii, Erica A.
0 n1 a* ^! Z+ N. K1 o) K' `( U, oGolemis
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; |1 a7 C  T# \1 S' N6 O. C16 A bacterial/yeast merged two-hybrid system: protocol for bacterial
3 n4 J( n" O3 S( ]- Escreening
! J# x6 E4 T* u1 @5 j/ I4 p) XIlya G. Serebriiskii, Nadia Milech, Erica A. Golemis4 i+ K. i9 E0 R
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17 Engineering Cys2His2 Zinc Finger Domains using a Bacterial
8 ~0 S# P: V& [) F0 U8 q: fCell-Based Two-Hybrid Selection System# k$ r' C5 [& ]# N0 h$ c: j) Z6 k
Stacey Thibodeau-Beganny and J. Keith Joung

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Functional Analysis Program
% u  Y% O; ~5 Y! K4 z( s$ }Overview
" ~$ K* g0 U# ], \Research Objectives
/ ^9 l8 C4 ~$ U6 g/ nPolicies, Reports and Related Project Information
# C9 `0 e; ]9 x% {+ n" n" O$ \4 w6 G" FFunding Opportunities ) p' I5 H) N7 E/ p8 B' p9 v0 e
Staff
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" W  q# N5 V6 n1 iFunctional Analysis Program Overview
3 q4 W7 G- [" U7 k( e1 M0 CCompletely 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.
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1 j+ i$ K7 J/ S5 c  u& q) @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).
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5 i, a& `( b+ O4 QTop of page
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Functional Analysis Program Research Objectives:   j$ p- `; q4 z: l7 l6 P, O- U* p3 K
Identification and mapping of all functional elements (both coding and non-coding) in a genome.1 G" @' [: E5 A1 i. r! d0 [* f

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4 H0 D, n* {* XGeneration of high-quality, full-length and representative cDNA libraries.  h. u) K/ b& e' O' ?2 q& ]

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Analysis 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.
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4 a8 H2 R+ a# E8 n7 u- ZAnalysis of naturally occurring or induced mutations that alter RNA and/or protein expression.
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Analysis of cellular localization of proteins and of protein-protein, or protein-nucleic acid, interactions.
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Comparative analysis of protein sequences.7 G% ]) r2 [$ l& n' Z1 D1 j; Z% m/ w
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9 M# F  L/ t+ [; z$ O5 A& pAnalysis of genome organization and its effect on cellular functions. : x7 U+ h+ V8 G. W* ]8 A4 t' p& h
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Functional Analysis Program Policies, Reports and Related Program Information
% c8 v( n( A: r! V4 t* y& dWorkshop Reports
4 u  \3 S8 m3 n, }- ?+ {8 GWorkshop on the Comprehensive Extraction of Biological Information from Genomic Sequence July 23 - 24, 2002
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Non-Mammalian Models Workshop [nih.gov] February 16-17, 19996 y: z+ E% ^3 m5 R
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Functional Analysis Workshop December 2-3, 1997+ p! m: v$ L+ x' C

+ L7 P' g5 ~! E) @% M2 p5 LRelated Projects' w8 y& r) `4 @( P, N& c5 v
ENCODE (Encyclopedia of DNA Elements)
% P% h5 f: H$ C2 O& G5 O6 iThe 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.
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  G' {" F1 N/ [- `7 JFull-length cDNA Project (The Mammalian Gene Collection) [mgc.nci.nih.gov]
" Q( m. Q1 }: E$ {  W9 q* |% uThe 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).% T* S, B7 G: c4 O8 q6 G
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Model Organisms for Biomedical Research [nih.gov]
. d  a# |* J/ z% EProvides information and relevant links for trans-NIH model organism initiatives and their related funding opportunities., J2 r( O2 a2 T8 S3 [" q

" v1 Q+ c1 M! a9 C/ pPolicies
9 F! g* P, x; B. D" [2 y% h/ nNHGRI Rapid Data Release Policy (January 2003)
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NIH-DOE Guidelines for Access to Mapping and Sequencing Data and Material Resources (Spring 1998)4 g8 h/ Z% i/ v% p- {) g

1 ?8 D, M4 }7 VFor 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]" m9 X8 U' [  H7 B* ^3 o
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4 ]9 x, G" L4 U. ]: GFunctional Analysis Program Funding Opportunities8 j1 G8 |+ W! i- R: f; m. t
Archival: PA-97-044: Technologies for Genomic Mapping, Sequencing and Analysis [Expired]
! X% e9 g1 W  P8 Q4 A! X7 r) xThis announcement solicited investigator-initiated proposals to develop new technologies./ A$ l2 Y8 @6 _2 l3 A1 V  R8 e/ h
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Centers of Excellence in Genomic Science (CEGS)4 k) ]0 N; N% \; Q3 H8 d

5 ?9 q. v, H1 iExpired Grant Solicitations
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Functional Analysis Program Staff% a* n7 j" i7 \& }, @+ D) }0 o% i7 P
Program Directors4 Y$ a& j; _- X
Elise Feingold, Ph.D.
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- a" N; o; Z: {* N* |Gary Temple, Ph.D.
: _1 F3 v( g& h5 t' e" g8 uE-mail: gtemple@mail.nih.gov( P4 \( l! F+ v* F; ]; I# F

4 Z9 H% {; t% ]. ~7 TBettie Graham, Ph.D.
+ S0 X, z$ N1 U# S7 L3 nE-mail: grahamb@nhgri.nih.gov
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0 K' e% G1 W8 H( d; NProgram Analysts
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Cristen Robinson
% E7 i* c: }; y" o% O) FE-mail: robinsoncr@mail.nih.gov2 a4 P- F: R% K/ J6 I. p

4 m  g) _7 @% O& bAddress
$ u& K8 \2 ?& X0 I! E0 z* dNational Human Genome Research Institute
' _' Z$ I( F+ {0 m* M$ YNational Institutes of Health
* C# l' V; Y/ ], V5635 Fishers Lane, B# s+ C/ R2 g' u
Suite 4076, MSC 9305
% ~8 H& C6 [$ r0 ?$ O" g' G( ABethesda, MD 20892-9305
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Phone: (301) 496-7531
' L. z; c+ p; W* HFax: (301) 480-2770