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TGPred

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0.1.0

TGPred-0.1.0-py3-none-any.whl

Wheel Details

Project:	TGPred
Version:	0.1.0
Filename:	TGPred-0.1.0-py3-none-any.whl
Download:	[link]
Size:	11577
MD5:	`07720a0a3c03dab894963c5ad50665a8`
SHA256:	`770212c64918c525e113661e253cc917d2ecff3d50daa77cb327ebf8e6494ac1`
Uploaded:	2022-09-22 11:22:43 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version:	2.1
Name:	TGPred
Version:	0.1.0
Summary:	TGPred: Efficient methods for predicting target genes of a transcription factor by integrating statistics, machine learning, and optimization.
Author:	Ling Zhang
Author-Email:	lingzhan[at]mtu.edu
Home-Page:	https://github.com/tobefuture/TGPred
Classifier:	Programming Language :: Python :: 3
Classifier:	License :: OSI Approved :: MIT License
Classifier:	Operating System :: OS Independent
Requires-Python:	>=3.6
Requires-Dist:	numpy
Requires-Dist:	pandas
Requires-Dist:	cvxpy
Requires-Dist:	networkx
Requires-Dist:	sklearn
Description-Content-Type:	text/markdown
License-File:	LICENSE

[Description omitted; length: 1006 characters]

WHEEL

Wheel-Version:	1.0
Generator:	bdist_wheel (0.36.2)
Root-Is-Purelib:	true
Tag:	py3-none-any

RECORD

Path	Digest	Size
TGPred/TGPred.py	sha256=EC5mUhSGMoLjeVqtNrwiwjtEAdJ2jDZ8UJK7dRqRkX0	73407
TGPred/__init__.py	sha256=WK-M3TtVlQVzOb3VXuwrVmsVH1zdVybYWxZGKtLZs4A	231
TGPred-0.1.0.dist-info/LICENSE	sha256=N5SZG59cb6QGwLFJRFM3B0JMYhmWYDJrs90NQ3QF9BA	1067
TGPred-0.1.0.dist-info/METADATA	sha256=bE-2ETmZtHsXLD3G8v_3x2EFxyg1go3DK9TA_m-I4wU	1684
TGPred-0.1.0.dist-info/WHEEL	sha256=OqRkF0eY5GHssMorFjlbTIq072vpHpF60fIQA6lS9xA	92
TGPred-0.1.0.dist-info/top_level.txt	sha256=jEynjTC2xYd1z6sYehAOPfRo0uY99W89mvF3C62zsr4	7
TGPred-0.1.0.dist-info/RECORD	—	—

top_level.txt

TGPred