Create landingpage.rst

docs/source/landingpage.rst

@@ -0,0 +1,53 @@
+.. raw:: html
+
+    <div align="center">
+
+.. image:: source/_static/logo.jpg
+   :alt: logo
+   :width: 500
+
+.. raw:: html
+
+    </div>
+
+.. image:: https://img.shields.io/pypi/v/GENetLib?logo=Pypi
+    :target: https://pypi.org/project/GENetLib
+    :alt: PyPIversion
+.. image:: https://img.shields.io/badge/Python-3.8%2B-lightblue.svg
+    :target: https://pypi.org/project/GENetLib
+    :alt: Pythonversion
+.. image:: https://github.com/Barry57/GENetLib/actions/workflows/CI.yml/badge.svg
+    :target: https://github.com/Barry57/GENetLib/actions/workflows/CI.yml/badge.svg
+    :alt: CI
+.. image:: https://codecov.io/github/Barry57/GENetLib/graph/badge.svg?token=9J9QMN7L9Z
+    :target: https://codecov.io/github/Barry57/GENetLib
+    :alt: Codecov
+.. image:: https://img.shields.io/badge/License-MIT-darkgreen.svg
+    :target: https://opensource.org/licenses/MIT
+    :alt: License
+.. image:: https://img.shields.io/badge/License-MIT-darkgreen.svg
+    :target: https://opensource.org/licenses/MIT
+    :alt: Codestyle
+
+
+``GENetLib``: A Python Library for Gene–environment Interaction Analysis via Deep Learning
+================================================================================
+
+``GENetLib`` is a Python library designed for gene-environment interaction analysis via neural network, addressing the analytical challenges in complex disease research. This package is capable of handling a variety of input data types:
+
+- Scalar input data
+- Functional input data (or densely measured data)
+
+This package also supports diverse output requirements:
+
+- Continuous output data
+- Binary output data
+- Survival output data
+
+By integrating minimax concave penalty (MCP) and L2-norm regularization within a neural network estimation framework, ``GENetLib`` offers an innovative solution for high-dimensional genetic data analysis. The framework is shown below.
+
+.. image:: image/framework.png
+   :alt: framework
+   :width: 600
+
+We provide a web-based documentation which introduces the meaning of function parameters, the usage of functions, detailed information about methods, and gives examples for each. The web page is available at `documentations <https://open-box.readthedocs.io/en/latest/>`_. This package has been uploaded to PyPI with previous versions, and the web page is available at `PyPI package <https://pypi.org/project/genetlib/>`_. Users can also check `tags <https://github.com/Barry57/GENetLib/releases>`_ to get historical versions.