enviPy-bayer/templates/static/about_us.html

{% extends "framework_modern.html" %}
{% load static %}

{% block main_content %}
  <div class="mx-auto max-w-4xl px-4 py-8">
    <!-- Breadcrumbs -->
    <div class="breadcrumbs mb-4 text-sm">
      <ul>
        <li><a href="/">Home</a></li>
        <li>About Us</li>
      </ul>
    </div>

    <!-- Main Content -->
    <div class="bg-base-100 rounded-lg p-8 shadow-xl">
      <h1 class="mb-6 text-4xl font-bold">About enviPath</h1>

      <div class="prose max-w-none">
        <!-- Hero Image/Graphic -->
        <div class="mb-8">
          <img
            src="{% static '/images/ep-rule-artwork.png' %}"
            alt="enviPath System"
            class="mx-auto w-full max-w-2xl rounded-lg shadow-md"
          />
        </div>

        <p class="mb-6 text-lg">
          enviPath is a comprehensive database and prediction system for the
          microbial biotransformation of organic environmental contaminants.
          Since 2015, we have been at the forefront of computational
          environmental chemistry, helping researchers understand and predict
          biodegradation pathways.
        </p>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">Our Mission</h2>
        <p class="mb-4">
          Our mission is to advance environmental science through innovative
          computational tools that predict and analyze the biotransformation of
          chemical compounds. We strive to provide researchers, regulators, and
          industry professionals with accurate, accessible tools for
          understanding environmental fate and behavior.
        </p>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">What We Offer</h2>
        <div class="mb-6 grid gap-6 md:grid-cols-2">
          <div class="card bg-base-200 shadow-md">
            <div class="card-body">
              <h3 class="card-title text-primary">Pathway Database</h3>
              <p>
                Access experimentally observed biotransformation pathways and
                reactions from curated scientific literature.
              </p>
            </div>
          </div>
          <div class="card bg-base-200 shadow-md">
            <div class="card-body">
              <h3 class="card-title text-primary">Prediction System</h3>
              <p>
                Use our relative reasoning models to predict likely
                biotransformation pathways and products for new compounds.
              </p>
            </div>
          </div>
          <div class="card bg-base-200 shadow-md">
            <div class="card-body">
              <h3 class="card-title text-primary">Machine Learning Models</h3>
              <p>
                Leverage advanced ML algorithms trained on extensive
                biodegradation data for accurate predictions.
              </p>
            </div>
          </div>
          <div class="card bg-base-200 shadow-md">
            <div class="card-body">
              <h3 class="card-title text-primary">Community Platform</h3>
              <p>
                Join our active community of researchers to share knowledge,
                discuss findings, and collaborate.
              </p>
            </div>
          </div>
        </div>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">Our Technology</h2>
        <p class="mb-4">
          enviPath employs a unique combination of rule-based and machine
          learning approaches to predict biotransformation pathways:
        </p>
        <ul class="mb-4 list-inside list-disc space-y-2">
          <li>
            <strong>Relative Reasoning:</strong> Uses structural similarity to
            known biotransformations
          </li>
          <li>
            <strong>Rule-Based Systems:</strong> Applies expert-curated
            transformation rules
          </li>
          <li>
            <strong>Machine Learning:</strong> Leverages neural networks for
            pattern recognition
          </li>
          <li>
            <strong>Hybrid Models:</strong> Combines multiple approaches for
            optimal accuracy
          </li>
        </ul>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">Our Partners</h2>
        <p class="mb-4">
          enviPath is backed by leading research institutions and collaborators:
        </p>
        <div class="my-8 flex flex-wrap items-center justify-center gap-8">
          <img
            src="{% static '/images/uoa-logo-small.png' %}"
            alt="The University of Auckland"
            class="h-20 object-contain"
          />
          <img
            src="{% static '/images/logo-eawag.svg' %}"
            alt="Eawag"
            class="h-16 object-contain"
          />
          <img
            src="{% static '/images/uzh-logo.svg' %}"
            alt="University of Zurich"
            class="h-20 object-contain"
          />
        </div>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">Our Team</h2>
        <p class="mb-4">
          enviPath is developed and maintained by a dedicated team of
          computational chemists, environmental scientists, and software
          engineers. Our interdisciplinary approach ensures that the platform
          meets the needs of the scientific community while remaining accessible
          and user-friendly.
        </p>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">Research Impact</h2>
        <p class="mb-4">
          Since its inception, enviPath has contributed to numerous scientific
          publications and environmental assessments. Our tools are used by:
        </p>
        <ul class="mb-4 list-inside list-disc space-y-2">
          <li>
            Academic researchers in environmental chemistry and toxicology
          </li>
          <li>Regulatory agencies for chemical risk assessment</li>
          <li>
            Chemical manufacturers for product development and safety evaluation
          </li>
          <li>Environmental consultants for contamination studies</li>
        </ul>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">
          Open Science Commitment
        </h2>
        <p class="mb-4">
          We are committed to open science principles. enviPath provides free
          access to our database and prediction tools for academic research. We
          actively contribute to the scientific community through publications,
          open-source software, and collaboration.
        </p>

        <div class="card bg-primary text-primary-content mt-8">
          <div class="card-body">
            <h3 class="card-title">Get Involved</h3>
            <p>
              Join our community, contribute data, or collaborate on research
              projects.
            </p>
            <div class="card-actions mt-4 justify-end">
              <a
                href="https://community.envipath.org/"
                target="_blank"
                class="btn btn-secondary"
                >Visit Community</a
              >
              <a href="/contact" class="btn btn-ghost">Contact Us</a>
            </div>
          </div>
        </div>

        <h2 class="mt-8 mb-4 text-2xl font-semibold">Publications</h2>
        <p class="mb-4">
          To learn more about the science behind enviPath, please visit our
          <a href="/cite" class="link link-primary">citations page</a> for key
          publications and how to cite our work.
        </p>
      </div>
    </div>
  </div>
{% endblock main_content %}