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h5 指数:165
h5 中位数:296

h5 指数是指在过去整整 5 年中所发表文章的 h 指数。h 指在 2017-2021 年间发表的 h 篇文章每篇至少都被引用过 h 次的最大值。隐藏

出版物的 h5 中位数，是指出版物的 h5 指数所涵盖的所有文章获得的引用次数的中位值。隐藏

标题/作者	引用次数	年份
SciPy 1.0: fundamental algorithms for scientific computing in Python P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ... Nature Methods 17 (3), 261-272	10950	2020
ModelFinder: fast model selection for accurate phylogenetic estimates S Kalyaanamoorthy, BQ Minh, TKF Wong, A von Haeseler, LS Jermiin Nature Methods 14 (6), 587-589	5206	2017
Salmon provides fast and bias-aware quantification of transcript expression R Patro, G Duggal, MI Love, RA Irizarry, C Kingsford Nature Methods 14 (4), 417-419	4417	2017
MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy SQ Zheng, E Palovcak, JP Armache, KA Verba, Y Cheng, DA Agard Nature Methods 14 (4), 331-332	3780	2017
cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination A Punjani, JL Rubinstein, DJ Fleet, MA Brubaker Nature Methods 14 (3), 290-296	2528	2017
CHARMM36m: an improved force field for folded and intrinsically disordered proteins J Huang, S Rauscher, G Nawrocki, T Ran, M Feig, BL de Groot, ... Nature Methods 14 (1), 71-73	2241	2017
Reversed graph embedding resolves complex single-cell trajectories X Qiu, Q Mao, Y Tang, L Wang, R Chawla, HA Pliner, C Trapnell Nature Methods 14 (10), 979-982	1618	2017
SCENIC: single-cell regulatory network inference and clustering S Aibar, CB González-Blas, T Moerman, VA Huynh-Thu, H Imrichova, ... Nature Methods 14 (11), 1083-1086	1460	2017
Simultaneous epitope and transcriptome measurement in single cells M Stoeckius, C Hafemeister, W Stephenson, B Houck-Loomis, ... Nature Methods 14 (9), 865-868	1360	2017
Fast, sensitive and accurate integration of single-cell data with Harmony I Korsunsky, N Millard, J Fan, K Slowikowski, F Zhang, K Wei, ... Nature Methods 16 (12), 1289-1296	1180	2019
fMRIPrep: a robust preprocessing pipeline for functional MRI O Esteban, CJ Markiewicz, RW Blair, CA Moodie, AI Isik, A Erramuzpe, ... Nature Methods 16 (1), 111-116	1040	2019
Differential analysis of RNA-seq incorporating quantification uncertainty H Pimentel, NL Bray, S Puente, P Melsted, L Pachter Nature Methods 14 (7), 687-690	992	2017
An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues MR Corces, AE Trevino, EG Hamilton, PG Greenside, ... Nature Methods 14 (10), 959-962	984	2017
SC3: consensus clustering of single-cell RNA-seq data VY Kiselev, K Kirschner, MT Schaub, T Andrews, A Yiu, T Chandra, ... Nature Methods 14 (5), 483-486	938	2017
U-Net: deep learning for cell counting, detection, and morphometry T Falk, D Mai, R Bensch, Ö Çiçek, A Abdulkadir, Y Marrakchi, A Böhm, ... Nature Methods 16 (1), 67-70	890	2019
Species-level functional profiling of metagenomes and metatranscriptomes EA Franzosa, LJ McIver, G Rahnavard, LR Thompson, M Schirmer, ... Nature Methods 15 (11), 962-968	840	2018
Moving beyond P values: data analysis with estimation graphics J Ho, T Tumkaya, S Aryal, H Choi, A Claridge-Chang Nature Methods 16 (7), 565-566	831	2019
Single-cell mRNA quantification and differential analysis with Census X Qiu, A Hill, J Packer, D Lin, YA Ma, C Trapnell Nature Methods 14 (3), 309-315	809	2017
Accurate detection of complex structural variations using single-molecule sequencing FJ Sedlazeck, P Rescheneder, M Smolka, H Fang, M Nattestad, ... Nature Methods 15 (6), 461-468	760	2018
Points of Significance: Principal component analysis J Lever, M Krzywinski, N Altman Nature Methods 14 (7), 641-643	748	2017

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