-
1
-
-
22844457491
-
DNA methylation and human disease
-
Robertson KD. DNA methylation and human disease. Nat Rev Genet. 2005;6:597-610.
-
(2005)
Nat Rev Genet
, vol.6
, pp. 597-610
-
-
Robertson, K.D.1
-
2
-
-
43749098985
-
DNA methylation landscapes: provocative insights from epigenomics
-
Suzuki MM, Bird A. DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet. 2008;9:465-76.
-
(2008)
Nat Rev Genet
, vol.9
, pp. 465-476
-
-
Suzuki, M.M.1
Bird, A.2
-
3
-
-
77249137168
-
Principles and challenges of genome-wide DNA methylation analysis
-
Laird PW. Principles and challenges of genome-wide DNA methylation analysis. Nat Rev Genet. 2010;11:191-203.
-
(2010)
Nat Rev Genet
, vol.11
, pp. 191-203
-
-
Laird, P.W.1
-
4
-
-
84863986133
-
Functions of DNA methylation: islands, start sites, gene bodies and beyond
-
Jones PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet. 2012;13:484-92.
-
(2012)
Nat Rev Genet
, vol.13
, pp. 484-492
-
-
Jones, P.A.1
-
5
-
-
84905405443
-
Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity
-
Smallwood SA, Lee HJ, Angermueller C, Krueger F, Saadeh H, Peat J, et al. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods. 2014;11:817-20.
-
(2014)
Nat Methods
, vol.11
, pp. 817-820
-
-
Smallwood, S.A.1
Lee, H.J.2
Angermueller, C.3
Krueger, F.4
Saadeh, H.5
Peat, J.6
-
6
-
-
84924601067
-
Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics
-
Farlik M, Sheffield NC, Nuzzo A, Datlinger P, Schönegger A, Klughammer J, et al. Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics. Cell Rep. 2015;10:1386-97.
-
(2015)
Cell Rep
, vol.10
, pp. 1386-1397
-
-
Farlik, M.1
Sheffield, N.C.2
Nuzzo, A.3
Datlinger, P.4
Schönegger, A.5
Klughammer, J.6
-
7
-
-
84890526238
-
Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing
-
Guo H, Zhu P, Wu X, Li X, Wen L, Tang F. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Res. 2013;23:2126-35.
-
(2013)
Genome Res
, vol.23
, pp. 2126-2135
-
-
Guo, H.1
Zhu, P.2
Wu, X.3
Li, X.4
Wen, L.5
Tang, F.6
-
8
-
-
84960091878
-
Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas
-
Hou Y, Guo H, Cao C, Li X, Hu B, Zhu P, et al. Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res. 2016;26:304-19.
-
(2016)
Cell Res
, vol.26
, pp. 304-319
-
-
Hou, Y.1
Guo, H.2
Cao, C.3
Li, X.4
Hu, B.5
Zhu, P.6
-
9
-
-
84919863433
-
Genome-wide bisulfite sequencing in zygotes identifies demethylation targets and maps the contribution of TET3 oxidation
-
Peat JR, Dean W, Clark SJ, Krueger F, Smallwood SA, Ficz G, et al. Genome-wide bisulfite sequencing in zygotes identifies demethylation targets and maps the contribution of TET3 oxidation. Cell Rep. 2014;9:1990-2000.
-
(2014)
Cell Rep
, vol.9
, pp. 1990-2000
-
-
Peat, J.R.1
Dean, W.2
Clark, S.J.3
Krueger, F.4
Smallwood, S.A.5
Ficz, G.6
-
10
-
-
84959255113
-
Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity
-
Angermueller C, Clark SJ, Lee HJ, Macaulay IC, Teng MJ, Hu TX, et al. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat Methods. 2016;13:229-32.
-
(2016)
Nat Methods
, vol.13
, pp. 229-232
-
-
Angermueller, C.1
Clark, S.J.2
Lee, H.J.3
Macaulay, I.C.4
Teng, M.J.5
Hu, T.X.6
-
11
-
-
84965048064
-
Simultaneous profiling of transcriptome and DNA methylome from a single cell
-
Hu Y, Huang K, An Q, Du G, Hu G, Xue J, et al. Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol. 2016;16:14.
-
(2016)
Genome Biol.
, vol.16
, pp. 14
-
-
Hu, Y.1
Huang, K.2
An, Q.3
Du, G.4
Hu, G.5
Xue, J.6
-
12
-
-
84939205466
-
Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements
-
Zhang W, Spector TD, Deloukas P, Bell JT, Engelhardt BE. Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements. Genome Biol. 2015;16:14.
-
(2015)
Genome Biol
, vol.16
, pp. 14
-
-
Zhang, W.1
Spector, T.D.2
Deloukas, P.3
Bell, J.T.4
Engelhardt, B.E.5
-
13
-
-
84883719710
-
Estimating absolute methylation levels at single-CpG resolution from methylation enrichment and restriction enzyme sequencing methods
-
Stevens M, Cheng JB, Li D, Xie M, Hong C, Maire CL, et al. Estimating absolute methylation levels at single-CpG resolution from methylation enrichment and restriction enzyme sequencing methods. Genome Res. 2013;23:1541-53.
-
(2013)
Genome Res
, vol.23
, pp. 1541-1553
-
-
Stevens, M.1
Cheng, J.B.2
Li, D.3
Xie, M.4
Hong, C.5
Maire, C.L.6
-
14
-
-
84926632357
-
Large-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues
-
Ernst J, Kellis M. Large-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues. Nat Biotechnol. 2015;33:364-76.
-
(2015)
Nat Biotechnol
, vol.33
, pp. 364-376
-
-
Ernst, J.1
Kellis, M.2
-
15
-
-
84923361176
-
iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition
-
Liu Z, Xiao X, Qiu W-R, Chou K-C. iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition. Anal Biochem. 2015;474:69-77.
-
(2015)
Anal Biochem
, vol.474
, pp. 69-77
-
-
Liu, Z.1
Xiao, X.2
Qiu, W.-R.3
Chou, K.-C.4
-
16
-
-
84923779988
-
Predicting the human epigenome from DNA motifs
-
Whitaker JW, Chen Z, Wang W. Predicting the human epigenome from DNA motifs. Nat Methods. 2015;12:265-72.
-
(2015)
Nat Methods
, vol.12
, pp. 265-272
-
-
Whitaker, J.W.1
Chen, Z.2
Wang, W.3
-
17
-
-
0000359337
-
Backpropagation applied to handwritten zip code recognition
-
LeCun Y, Boser B, Denker JS, Henderson D, Howard RE, Hubbard W, et al. Backpropagation applied to handwritten zip code recognition. Neural Comput. 1989;1:541-51.
-
(1989)
Neural Comput
, vol.1
, pp. 541-551
-
-
LeCun, Y.1
Boser, B.2
Denker, J.S.3
Henderson, D.4
Howard, R.E.5
Hubbard, W.6
-
20
-
-
23644439586
-
Prediction of methylated CpGs in DNA sequences using a support vector machine
-
Bhasin M, Zhang H, Reinherz EL, Reche PA. Prediction of methylated CpGs in DNA sequences using a support vector machine. FEBS Lett. 2005;579:4302-8.
-
(2005)
FEBS Lett
, vol.579
, pp. 4302-4308
-
-
Bhasin, M.1
Zhang, H.2
Reinherz, E.L.3
Reche, P.A.4
-
21
-
-
84872895742
-
Predicting DNA, methylation status using word composition
-
Lu L. Predicting DNA, methylation status using word composition. J Biomed Sci Eng. 2010;3:672-6.
-
(2010)
J Biomed Sci Eng
, vol.3
, pp. 672-676
-
-
Lu, L.1
-
22
-
-
84858159518
-
Prediction of methylation CpGs and their methylation degrees in human DNA sequences
-
Zhou X, Li Z, Dai Z, Zou X. Prediction of methylation CpGs and their methylation degrees in human DNA sequences. Comput Biol Med. 2012;42:408-13.
-
(2012)
Comput Biol Med
, vol.42
, pp. 408-413
-
-
Zhou, X.1
Li, Z.2
Dai, Z.3
Zou, X.4
-
23
-
-
84896839862
-
The prediction of methylation states in human DNA sequences based on hexanucleotide composition and feature selection
-
Li Z, Chen L, Lai Y, Dai Z, Zou X. The prediction of methylation states in human DNA sequences based on hexanucleotide composition and feature selection. Anal Methods. 2014;6:1897.
-
(2014)
Anal Methods
, vol.6
, pp. 1897
-
-
Li, Z.1
Chen, L.2
Lai, Y.3
Dai, Z.4
Zou, X.5
-
25
-
-
84990890375
-
Character-level convolutional networks for text classification
-
arXiv
-
Zhang X, Zhao J, LeCun Y. Character-level convolutional networks for text classification. arXiv. 2015.
-
(2015)
-
-
Zhang, X.1
Zhao, J.2
LeCun, Y.3
-
26
-
-
84958589374
-
Deep residual learning for image recognition
-
arXiv
-
He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. arXiv. 2015.
-
(2015)
-
-
He, K.1
Zhang, X.2
Ren, S.3
Sun, J.4
-
27
-
-
84983383396
-
Inception-v4, Inception-ResNet and the impact of residual connections on learning
-
arXiv
-
Szegedy C, Ioffe S, Vanhoucke V. Inception-v4, Inception-ResNet and the impact of residual connections on learning. arXiv. 2016.
-
(2016)
-
-
Szegedy, C.1
Ioffe, S.2
Vanhoucke, V.3
-
28
-
-
84970899194
-
Deep modeling of gene expression regulation in an erythropoiesis model
-
Denas O, Taylor J. Deep modeling of gene expression regulation in an erythropoiesis model. Represent. Learn. ICML Workshop. 2013
-
(2013)
Represent. Learn. ICML Workshop
-
-
Denas, O.1
Taylor, J.2
-
29
-
-
84938888109
-
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
-
Alipanahi B, Delong A, Weirauch MT, Frey BJ. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nat Biotechnol. 2015;33:831-8.
-
(2015)
Nat Biotechnol
, vol.33
, pp. 831-838
-
-
Alipanahi, B.1
Delong, A.2
Weirauch, M.T.3
Frey, B.J.4
-
30
-
-
84958257565
-
Predicting effects of noncoding variants with deep learning-based sequence model
-
Zhou J, Troyanskaya OG. Predicting effects of noncoding variants with deep learning-based sequence model. Nat Methods. 2015;12:931-4.
-
(2015)
Nat Methods
, vol.12
, pp. 931-934
-
-
Zhou, J.1
Troyanskaya, O.G.2
-
31
-
-
84923276179
-
The human splicing code reveals new insights into the genetic determinants of disease
-
Xiong HY, Alipanahi B, Lee LJ, Bretschneider H, Merico D, Yuen RKC, et al. The human splicing code reveals new insights into the genetic determinants of disease. Science. 2015;347:1254806.
-
(2015)
Science
, vol.347
, pp. 1254806
-
-
Xiong, H.Y.1
Alipanahi, B.2
Lee, L.J.3
Bretschneider, H.4
Merico, D.5
Yuen, R.K.C.6
-
32
-
-
84976908652
-
Basset: Learning the Regulatory Code of the Accessible Genome with Deep Convolutional Neural Networks
-
Kelley DR, Snoek J, Rinn J. "Basset: Learning the Regulatory Code of the Accessible Genome with Deep Convolutional Neural Networks". Genom Res. doi: 10.1101/gr.200535.115.
-
Genom Res.
-
-
Kelley, D.R.1
Snoek, J.2
Rinn, J.3
-
34
-
-
0020480251
-
Use of the "Perceptron" algorithm to distinguish translational initiation sites in E. coli
-
Stormo GD, Schneider TD, Gold L, Ehrenfeucht A. Use of the "Perceptron" algorithm to distinguish translational initiation sites in E. coli. Nucleic Acids Res. 1982;10:2997-3011.
-
(1982)
Nucleic Acids Res
, vol.10
, pp. 2997-3011
-
-
Stormo, G.D.1
Schneider, T.D.2
Gold, L.3
Ehrenfeucht, A.4
-
35
-
-
33747885942
-
On counting position weight matrix matches in a sequence, with application to discriminative motif finding
-
Sinha S. On counting position weight matrix matches in a sequence, with application to discriminative motif finding. Bioinformatics. 2006;22:e454-63.
-
(2006)
Bioinformatics
, vol.22
, pp. e454-e463
-
-
Sinha, S.1
-
36
-
-
84939821078
-
Empirical evaluation of gated recurrent neural networks on sequence modeling
-
arXiv
-
Chung J, Gulcehre C, Cho K, Bengio Y. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv. 2014.
-
(2014)
-
-
Chung, J.1
Gulcehre, C.2
Cho, K.3
Bengio, Y.4
-
37
-
-
0035478854
-
Random forests
-
Breiman L. Random forests. Mach Learn. 2001;45:5-32.
-
(2001)
Mach Learn
, vol.45
, pp. 5-32
-
-
Breiman, L.1
-
38
-
-
84864758525
-
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation
-
Powers DM. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. J Mach Learn Technol. 2011;2:37-63.
-
(2011)
J Mach Learn Technol
, vol.2
, pp. 37-63
-
-
Powers, D.M.1
-
39
-
-
0016772212
-
Comparison of the predicted and observed secondary structure of T4 phage lysozyme
-
Matthews BW. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta. 1975;405:442-51.
-
(1975)
Biochim Biophys Acta
, vol.405
, pp. 442-451
-
-
Matthews, B.W.1
-
40
-
-
77951116072
-
CpG islands influence chromatin structure via the CpG-binding protein Cfp1
-
Thomson JP, Skene PJ, Selfridge J, Clouaire T, Guy J, Webb S, et al. CpG islands influence chromatin structure via the CpG-binding protein Cfp1. Nature. 2010;464:1082-6.
-
(2010)
Nature
, vol.464
, pp. 1082-1086
-
-
Thomson, J.P.1
Skene, P.J.2
Selfridge, J.3
Clouaire, T.4
Guy, J.5
Webb, S.6
-
41
-
-
78650684739
-
GC-rich sequence elements recruit PRC2 in mammalian ES cells
-
Mendenhall EM, Koche RP, Truong T, Zhou VW, Issac B, Chi AS, et al. GC-rich sequence elements recruit PRC2 in mammalian ES cells. PLoS Genet. 2010;6:e1001244.
-
(2010)
PLoS Genet
, vol.6
-
-
Mendenhall, E.M.1
Koche, R.P.2
Truong, T.3
Zhou, V.W.4
Issac, B.5
Chi, A.S.6
-
42
-
-
84907413210
-
Determination and inference of eukaryotic transcription factor sequence specificity
-
Weirauch MT, Yang A, Albu M, Cote AG, Montenegro-Montero A, Drewe P, et al. Determination and inference of eukaryotic transcription factor sequence specificity. Cell. 2014;158:1431-43.
-
(2014)
Cell
, vol.158
, pp. 1431-1443
-
-
Weirauch, M.T.1
Yang, A.2
Albu, M.3
Cote, A.G.4
Montenegro-Montero, A.5
Drewe, P.6
-
43
-
-
58149200952
-
UniPROBE: an online database of protein binding microarray data on protein-DNA interactions
-
Newburger DE, Bulyk ML. UniPROBE: an online database of protein binding microarray data on protein-DNA interactions. Nucleic Acids Res. 2009;37:D77-82.
-
(2009)
Nucleic Acids Res
, vol.37
, pp. D77-82
-
-
Newburger, D.E.1
Bulyk, M.L.2
-
44
-
-
73449113904
-
Dnmt3/transcription factor interactions as crucial players in targeted DNA methylation
-
Hervouet E, Vallette FM, Cartron P-F. Dnmt3/transcription factor interactions as crucial players in targeted DNA methylation. Epigenetics. 2009;4:487-99.
-
(2009)
Epigenetics
, vol.4
, pp. 487-499
-
-
Hervouet, E.1
Vallette, F.M.2
Cartron, P.-F.3
-
45
-
-
84890504504
-
Disclosing the crosstalk among DNA methylation, transcription factors, and histone marks in human pluripotent cells through discovery of DNA methylation motifs
-
Luu P-L, Scholer HR, Arauzo-Bravo MJ. Disclosing the crosstalk among DNA methylation, transcription factors, and histone marks in human pluripotent cells through discovery of DNA methylation motifs. Genome Res. 2013;23:2013-29.
-
(2013)
Genome Res
, vol.23
, pp. 2013-2029
-
-
Luu, P.-L.1
Scholer, H.R.2
Arauzo-Bravo, M.J.3
-
46
-
-
33947201809
-
Analysis of the vertebrate insulator protein CTCF-binding sites in the human genome
-
Kim TH, Abdullaev ZK, Smith AD, Ching KA, Loukinov DI, Green RD, et al. Analysis of the vertebrate insulator protein CTCF-binding sites in the human genome. Cell. 2007;128:1231-45.
-
(2007)
Cell
, vol.128
, pp. 1231-1245
-
-
Kim, T.H.1
Abdullaev, Z.K.2
Smith, A.D.3
Ching, K.A.4
Loukinov, D.I.5
Green, R.D.6
-
47
-
-
50649086353
-
Mouse development with a single E2F activator
-
Tsai S-Y, Opavsky R, Sharma N, Wu L, Naidu S, Nolan E, et al. Mouse development with a single E2F activator. Nature. 2008;454:1137-41.
-
(2008)
Nature
, vol.454
, pp. 1137-1141
-
-
Tsai, S.-Y.1
Opavsky, R.2
Sharma, N.3
Wu, L.4
Naidu, S.5
Nolan, E.6
-
48
-
-
79953172903
-
A functional family-wide screening of SP/KLF proteins identifies a subset of suppressors of KRAS -mediated cell growth
-
Fernandez-Zapico ME, Lomberk GA, Tsuji S, DeMars CJ, Bardsley MR, Lin Y-H, et al. A functional family-wide screening of SP/KLF proteins identifies a subset of suppressors of KRAS -mediated cell growth. Biochem J. 2011;435:529-37.
-
(2011)
Biochem J
, vol.435
, pp. 529-537
-
-
Fernandez-Zapico, M.E.1
Lomberk, G.A.2
Tsuji, S.3
DeMars, C.J.4
Bardsley, M.R.5
Lin, Y.-H.6
-
49
-
-
12944336527
-
Foxa2 is required for the differentiation of pancreatic α-cells
-
Lee CS, Sund NJ, Behr R, Herrera PL, Kaestner KH. Foxa2 is required for the differentiation of pancreatic α-cells. Dev Biol. 2005;278:484-95.
-
(2005)
Dev Biol
, vol.278
, pp. 484-495
-
-
Lee, C.S.1
Sund, N.J.2
Behr, R.3
Herrera, P.L.4
Kaestner, K.H.5
-
50
-
-
17144407948
-
Compensatory roles of Foxa1 and Foxa2 during lung morphogenesis
-
Wan H, Dingle S, Xu Y, Besnard V, Kaestner KH, Ang S-L, et al. Compensatory roles of Foxa1 and Foxa2 during lung morphogenesis. J Biol Chem. 2005;280:13809-16.
-
(2005)
J Biol Chem
, vol.280
, pp. 13809-13816
-
-
Wan, H.1
Dingle, S.2
Xu, Y.3
Besnard, V.4
Kaestner, K.H.5
Ang, S.-L.6
-
51
-
-
0027297647
-
The SRF accessory protein Elk-1 contains a growth factor-regulated transcriptional activation domain
-
Marais R, Wynne J, Treisman R. The SRF accessory protein Elk-1 contains a growth factor-regulated transcriptional activation domain. Cell. 1993;73:381-93.
-
(1993)
Cell
, vol.73
, pp. 381-393
-
-
Marais, R.1
Wynne, J.2
Treisman, R.3
-
52
-
-
0032476590
-
Serum response factor is essential for mesoderm formation during mouse embryogenesis
-
Arsenian S, Weinhold B, Oelgeschläger M, Rüther U, Nordheim A. Serum response factor is essential for mesoderm formation during mouse embryogenesis. EMBO J. 1998;17:6289-99.
-
(1998)
EMBO J
, vol.17
, pp. 6289-6299
-
-
Arsenian, S.1
Weinhold, B.2
Oelgeschläger, M.3
Rüther, U.4
Nordheim, A.5
-
53
-
-
80555156105
-
In embryonic stem cells, ZFP57/KAP1 recognize a methylated hexanucleotide to affect chromatin and DNA methylation of imprinting control regions
-
Quenneville S, Verde G, Corsinotti A, Kapopoulou A, Jakobsson J, Offner S, et al. In embryonic stem cells, ZFP57/KAP1 recognize a methylated hexanucleotide to affect chromatin and DNA methylation of imprinting control regions. Mol Cell. 2011;44:361-72.
-
(2011)
Mol Cell
, vol.44
, pp. 361-372
-
-
Quenneville, S.1
Verde, G.2
Corsinotti, A.3
Kapopoulou, A.4
Jakobsson, J.5
Offner, S.6
-
54
-
-
84975705235
-
IL-6 mediates differentiation disorder during spermatogenesis in obesity-associated inflammation by affecting the expression of Zfp637 through the SOCS3/STAT3 pathway
-
Huang G, Yuan M, Zhang J, Li J, Gong D, Li Y, et al. IL-6 mediates differentiation disorder during spermatogenesis in obesity-associated inflammation by affecting the expression of Zfp637 through the SOCS3/STAT3 pathway. Sci Rep. 2016;6:28012.
-
(2016)
Sci Rep
, vol.6
, pp. 28012
-
-
Huang, G.1
Yuan, M.2
Zhang, J.3
Li, J.4
Gong, D.5
Li, Y.6
-
55
-
-
84905220041
-
Deep inside convolutional networks: visualising image classification models and saliency maps
-
arXiv
-
Simonyan K, Vedaldi A, Zisserman A. Deep inside convolutional networks: visualising image classification models and saliency maps. arXiv. 2013.
-
(2013)
-
-
Simonyan, K.1
Vedaldi, A.2
Zisserman, A.3
-
56
-
-
84931834126
-
A pooling-based approach to mapping genetic variants associated with DNA methylation
-
Kaplow IM, MacIsaac JL, Mah SM, McEwen LM, Kobor MS, Fraser HB. A pooling-based approach to mapping genetic variants associated with DNA methylation. Genome Res. 2015;25:907-17.
-
(2015)
Genome Res
, vol.25
, pp. 907-917
-
-
Kaplow, I.M.1
MacIsaac, J.L.2
Mah, S.M.3
McEwen, L.M.4
Kobor, M.S.5
Fraser, H.B.6
-
57
-
-
0034067297
-
HMG20A and HMG20B map to human chromosomes 15q24 and 19p13.3 and constitute a distinct class of HMG-box genes with ubiquitous expression
-
Sumoy L, Carim L, Escarceller M, Nadal M, Gratacòs M, Pujana MA, et al. HMG20A and HMG20B map to human chromosomes 15q24 and 19p13.3 and constitute a distinct class of HMG-box genes with ubiquitous expression. Cytogenet Genome Res. 2000;88:62-7.
-
(2000)
Cytogenet Genome Res
, vol.88
, pp. 62-67
-
-
Sumoy, L.1
Carim, L.2
Escarceller, M.3
Nadal, M.4
Gratacòs, M.5
Pujana, M.A.6
-
58
-
-
84922389693
-
Neural machine translation by jointly learning to align and translate
-
arXiv
-
Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate. arXiv. 2014.
-
(2014)
-
-
Bahdanau, D.1
Cho, K.2
Bengio, Y.3
-
59
-
-
85018271332
-
Google's neural machine translation system: bridging the gap between human and machine translation
-
arXiv
-
Wu Y, Schuster M, Chen Z, Le QV, Norouzi M, Macherey W, et al. Google's neural machine translation system: bridging the gap between human and machine translation. arXiv. 2016.
-
(2016)
-
-
Wu, Y.1
Schuster, M.2
Chen, Z.3
Le, Q.V.4
Norouzi, M.5
Macherey, W.6
-
61
-
-
84980031342
-
DNA-level splice junction prediction using deep recurrent neural networks
-
arXiv
-
Lee B, Lee T, Na B, Yoon S. DNA-level splice junction prediction using deep recurrent neural networks. arXiv. 2015.
-
(2015)
-
-
Lee, B.1
Lee, T.2
Na, B.3
Yoon, S.4
-
62
-
-
84976413226
-
DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences
-
Quang D, Xie X. DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences. Nucleic Acids Res. 2016;44:e107.
-
(2016)
Nucleic Acids Res
, vol.44
-
-
Quang, D.1
Xie, X.2
-
63
-
-
84904163933
-
Dropout: a simple way to prevent neural networks from overfitting
-
Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R. Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res. 2014;15:1929-58.
-
(2014)
J Mach Learn Res
, vol.15
, pp. 1929-1958
-
-
Srivastava, N.1
Hinton, G.2
Krizhevsky, A.3
Sutskever, I.4
Salakhutdinov, R.5
-
64
-
-
79951563340
-
Understanding the difficulty of training deep feedforward neural networks
-
Glorot X, Bengio Y. Understanding the difficulty of training deep feedforward neural networks. Int Conf Artif Intell Stat. 2016
-
(2016)
Int Conf Artif Intell Stat.
-
-
Glorot, X.1
Bengio, Y.2
-
65
-
-
84941620184
-
Adam: a method for stochastic optimization
-
arXiv
-
Kingma D, Ba J. Adam: a method for stochastic optimization. arXiv. 2014.
-
(2014)
-
-
Kingma, D.1
Ba, J.2
-
66
-
-
84857855190
-
Random search for hyper-parameter optimization
-
Bergstra J, Bengio Y. Random search for hyper-parameter optimization. J Mach Learn Res. 2012;13:281-305.
-
(2012)
J Mach Learn Res
, vol.13
, pp. 281-305
-
-
Bergstra, J.1
Bengio, Y.2
-
67
-
-
84937942087
-
Theano: new features and speed improvements
-
arXiv
-
Bastien F, Lamblin P, Pascanu R, Bergstra J, Goodfellow I, Bergeron A, et al. Theano: new features and speed improvements. arXiv. 2012.
-
(2012)
-
-
Bastien, F.1
Lamblin, P.2
Pascanu, R.3
Bergstra, J.4
Goodfellow, I.5
Bergeron, A.6
-
68
-
-
84962029452
-
Keras: Theano-based deep learning library
-
Accessed 26 Mar
-
Chollet F. Keras: Theano-based deep learning library. https://github.com/fchollet/keras. Accessed 26 Mar 2017.
-
(2017)
-
-
Chollet, F.1
-
69
-
-
2142738304
-
WebLogo: a sequence logo generator
-
Crooks GE. WebLogo: a sequence logo generator. Genome Res. 2004;14:1188-90.
-
(2004)
Genome Res
, vol.14
, pp. 1188-1190
-
-
Crooks, G.E.1
-
70
-
-
67849122320
-
MEME Suite: tools for motif discovery and searching
-
Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, et al. MEME Suite: tools for motif discovery and searching. Nucleic Acids Res. 2009;37:W202-8.
-
(2009)
Nucleic Acids Res
, vol.37
, pp. W202-W208
-
-
Bailey, T.L.1
Boden, M.2
Buske, F.A.3
Frith, M.4
Grant, C.E.5
Clementi, L.6
-
71
-
-
23744458086
-
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
-
Siepel A. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15:1034-50.
-
(2005)
Genome Res
, vol.15
, pp. 1034-1050
-
-
Siepel, A.1
-
72
-
-
84936916896
-
Robust locally weighted regression and smoothing scatterplots
-
Cleveland WS. Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc. 1979;74:829-36.
-
(1979)
J Am Stat Assoc
, vol.74
, pp. 829-836
-
-
Cleveland, W.S.1
|