Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.
Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.
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DOI：
10.1371/journal.pcbi.1005791
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发表时间：
2017-10
影响因子：
4.3
通讯作者：
Jones DT
中科院分区：
文献类型：
--
作者：
Wan C;Lees JG;Minneci F;Orengo CA;Jones DT
准确的基因或蛋白质功能预测是后基因组时代的关键挑战。目前大多数方法在分子功能预测方面表现良好，但由于该功能域中基于序列的特征的能力有限，因此很难提供与生物过程功能相关的有用注释。在这项工作中，我们系统地评估了果蝇蛋白质功能预测的时间转录表达谱的预测能力。我们的结果表明，与单独的序列衍生特征相比，当基于转录表达谱的特征与序列衍生特征整合时，预测蛋白质功能的性能明显更好。我们还观察到，基于表达和基于序列的特征的组合可以进一步提高预测基因功能的所有三个领域的准确性。基于最佳特征组合，我们提出了一种新的基于多分类器的果蝇蛋白功能预测方法，FFPred-fly+。解释我们的机器学习模型还使我们能够确定果蝇的生物过程和发育阶段之间的一些潜在联系。尽管付出了艰苦的实验努力和基于广泛序列相似性的注释转移，UniProtKB 中不到一半的果蝇蛋白质序列具有一些功能注释。为了帮助填补这一空白，我们测试了公开可用的时间基因表达谱的有用性以及它们与许多可以有效地从相应蛋白质序列衍生的生物物理属性的组合。我们发现这种综合功能预测方法比单独使用序列数据提供更准确的预测，并且我们期望这些预测有助于缩小表征果蝇蛋白功能所需的实验测定的数量。我们通过强调预测的生物过程功能与果蝇发育阶段的已知事实之间的相关性来进行论证。
Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster. Despite painstaking experimental efforts and the extensive sequence similarity based annotation transfers, less than a half of the fruit fly protein sequences in UniProtKB have some functional annotation. To help fill in this gap, we test the usefulness of publicly available temporal gene expression profiles and their combination with many biophysical attributes that can be effectively derived from the corresponding protein sequence. We find that such an integrative function prediction method provides more accurate predictions than using sequence data alone and we expect these predictions to help narrow down the number of experimental assays required to characterise fly protein function. We demonstrate by highlighting correlations between predicted biological process functions and known facts about fly developmental stages.
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影响因子：
3.7
作者：
Minneci F;Piovesan D;Cozzetto D;Jones DT
通讯作者：
Jones DT
影响因子：
14.9
作者：
Hunter S;Jones P;Mitchell A;Apweiler R;Attwood TK;Bateman A;Bernard T;Binns D;Bork P;Burge S;de Castro E;Coggill P;Corbett M;Das U;Daugherty L;Duquenne L;Finn RD;Fraser M;Gough J;Haft D;Hulo N;Kahn D;Kelly E;Letunic I;Lonsdale D;Lopez R;Madera M;Maslen J;McAnulla C;McDowall J;McMenamin C;Mi H;Mutowo-Muellenet P;Mulder N;Natale D;Orengo C;Pesseat S;Punta M;Quinn AF;Rivoire C;Sangrador-Vegas A;Selengut JD;Sigrist CJ;Scheremetjew M;Tate J;Thimmajanarthanan M;Thomas PD;Wu CH;Yeats C;Yong SY
通讯作者：
Yong SY
影响因子：
64.8
作者：
Graveley BR;Brooks AN;Carlson JW;Duff MO;Landolin JM;Yang L;Artieri CG;van Baren MJ;Boley N;Booth BW;Brown JB;Cherbas L;Davis CA;Dobin A;Li R;Lin W;Malone JH;Mattiuzzo NR;Miller D;Sturgill D;Tuch BB;Zaleski C;Zhang D;Blanchette M;Dudoit S;Eads B;Green RE;Hammonds A;Jiang L;Kapranov P;Langton L;Perrimon N;Sandler JE;Wan KH;Willingham A;Zhang Y;Zou Y;Andrews J;Bickel PJ;Brenner SE;Brent MR;Cherbas P;Gingeras TR;Hoskins RA;Kaufman TC;Oliver B;Celniker SE
通讯作者：
Celniker SE
影响因子：
12.3
作者：
Jiang Y;Oron TR;Clark WT;Bankapur AR;D'Andrea D;Lepore R;Funk CS;Kahanda I;Verspoor KM;Ben-Hur A;Koo da CE;Penfold-Brown D;Shasha D;Youngs N;Bonneau R;Lin A;Sahraeian SM;Martelli PL;Profiti G;Casadio R;Cao R;Zhong Z;Cheng J;Altenhoff A;Skunca N;Dessimoz C;Dogan T;Hakala K;Kaewphan S;Mehryary F;Salakoski T;Ginter F;Fang H;Smithers B;Oates M;Gough J;Törönen P;Koskinen P;Holm L;Chen CT;Hsu WL;Bryson K;Cozzetto D;Minneci F;Jones DT;Chapman S;Bkc D;Khan IK;Kihara D;Ofer D;Rappoport N;Stern A;Cibrian-Uhalte E;Denny P;Foulger RE;Hieta R;Legge D;Lovering RC;Magrane M;Melidoni AN;Mutowo-Meullenet P;Pichler K;Shypitsyna A;Li B;Zakeri P;ElShal S;Tranchevent LC;Das S;Dawson NL;Lee D;Lees JG;Sillitoe I;Bhat P;Nepusz T;Romero AE;Sasidharan R;Yang H;Paccanaro A;Gillis J;Sedeño-Cortés AE;Pavlidis P;Feng S;Cejuela JM;Goldberg T;Hamp T;Richter L;Salamov A;Gabaldon T;Marcet-Houben M;Supek F;Gong Q;Ning W;Zhou Y;Tian W;Falda M;Fontana P;Lavezzo E;Toppo S;Ferrari C;Giollo M;Piovesan D;Tosatto SC;Del Pozo A;Fernández JM;Maietta P;Valencia A;Tress ML;Benso A;Di Carlo S;Politano G;Savino A;Rehman HU;Re M;Mesiti M;Valentini G;Bargsten JW;van Dijk AD;Gemovic B;Glisic S;Perovic V;Veljkovic V;Veljkovic N;Almeida-E-Silva DC;Vencio RZ;Sharan M;Vogel J;Kansakar L;Zhang S;Vucetic S;Wang Z;Sternberg MJ;Wass MN;Huntley RP;Martin MJ;O'Donovan C;Robinson PN;Moreau Y;Tramontano A;Babbitt PC;Brenner SE;Linial M;Orengo CA;Rost B;Greene CS;Mooney SD;Friedberg I;Radivojac P
通讯作者：
Radivojac P
DOI：
10.1007/978-1-4939-3743-1_5
发表时间：
2017-01-01
期刊：
GENE ONTOLOGY HANDBOOK
影响因子：
--
作者：
Cozzetto, Domenico;Jones, David T.
通讯作者：
Jones, David T.