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Projects: pypi: tqdm

https://packages.ecosyste.ms/registries/pypi.org/packages/tqdm

Fast, Extensible Progress Meter
133 versions
Latest release: almost 3 years ago
8,250 dependent packages
77,241,928 downloads last month

Science Score: 65/100
Starting Score: 100 points
Penalties:
  • -10 PyPI ecosystem
    General-purpose ecosystem
  • -15 No science keywords
    No scientific terms found in keywords/classifiers
  • -10 No science terms in description
    No scientific terms found in description
Very Likely Science (65)

Papers Mentioning tqdm 6

10.1186/s13073-021-00904-z
An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility
Cited by: 33
Author(s): Liuyang Wang, Thomas J Balmat, Alejandro L. Antonia, Florica J. Constantine, Ricardo Henao, Thomas W. Burke, Andy Ingham, Micah T. McClain, Ephraim L. Tsalik, Emily R Ko, Geoffrey S. Ginsburg, Mark DeLong, Xiling Shen, Christopher W. Woods, Elizabeth R. Hauser, Dennis C. Ko
Software Mentions: 13
Published: about 5 years ago
10.1186/s12859-021-04093-9
Machine learning predicts nucleosome binding modes of transcription factors
Cited by: 1
Author(s): K C Kishan, Sridevi K. Subramanya, Rui Li, Feng Cui
Software Mentions: 9
Published: about 5 years ago
10.3390/s21062039
Detecting Anomalous Transactions via an IoT Based Application: A Machine Learning Approach for Horse Racing Betting
Cited by: 2
Author(s): Moohong Min, Jemin Justin Lee, Hyunbeom Park, Kyung-Ho Lee
Software Mentions: 6
Published: over 5 years ago
10.1155/2021/6668985
Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19
Cited by: 20
Author(s): Nishant Jha, Deepak Prashar, Mamoon Rashid, Mohammad Shafiq, Razaullah Khan, Catalin I. Pruncu, Shams Tabrez Siddiqui, Manindra Kumar
Software Mentions: 4
Published: almost 5 years ago
10.1021/acs.chemmater.0c03738
Mechanistic Origin of Superionic Lithium Diffusion in Anion-Disordered Li<sub>6</sub>PS<sub>5</sub><i>X</i> Argyrodites
Cited by: 55
Author(s): Benjamin Morgan
Software Mentions: 3
Published: over 5 years ago
10.3389/fnins.2021.683426
Convolutional Neural Net Learning Can Achieve Production-Level Brain Segmentation in Structural Magnetic Resonance Imaging
Cited by: 12
Author(s): Evan Fletcher, Charles DeCarli, Audrey P. Fan, Alexander Knaack
Software Mentions: 2
Published: almost 5 years ago