ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL TECHNOLOGIES AND COMPUTATIONAL

1. ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL
TECHNOLOGIES AND COMPUTATIONAL METHODS
1 Dr. T. Balaji, 2 Veeranan Veeranan,
1 Associate Professor, 2 M.Sc. Computer Science,
1 PG Dept. of Computer Science, Govt. Arts College, Melur, India.
2 PG Dept. of Computer Science, Govt. Arts College, Melur, India.

2.  The paper highlights the important Geographic Information Systems (GIS) aids in
understanding animal habitats, migration patterns, and conservation planning.
 Role of digital resources, communication technology, and Artificial Intelligence in
Biological research.
 AI techniques, Machine Learning and Deep Learning, bioinformatics tools develop
biological data analysis, enabling species identification and DNA segment prediction.
 Morphological Algorithms encouragement in species identification and population
monitoring.
 Soft computing techniques, including Fuzzy Sets, Evolutionary Algorithms, and others,
are crucial in addressing intricate challenges in bioinformatics and molecular biology,
such as protein classification, drug discovery.
INTRODUCTION

3. Digital
Resources,
Communication
Technology
Geographic
Information
Systems
AI
techniques,
Machine
Learning
and
Deep
Learning
Morphological
Algorithms
and
Soft
Computing
ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL TECHNOLOGIES AND
COMPUTATIONAL METHODS

4. Digital
Resources,
Communication
Technology
AI
techniques,
Machine
Learning
and
Deep
Learning
Morphological
Algorithms
and
Soft
Computing
ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL TECHNOLOGIES AND
COMPUTATIONAL METHODS
Geographic
Information
Systems
 GIS also aids in conservation planning by identifying
priority areas for conservation efforts.
 It tracks wildlife populations using GPS tracking
information, creating dynamic population models.

5. Geographic
Information
Systems
AI
techniques,
Machine
Learning
and
Deep
Learning
Morphological
Algorithms
and
Soft
Computing
ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL TECHNOLOGIES AND
COMPUTATIONAL METHODS
Digital
resources,
Communication
Technology
 Online databases like GenBank, UniProt, NCBI, and Ensembl provide
access to genomic and proteomic data.
 Statistical software packages like R and MATLAB.
 Online learning platforms like Coursera, and Bioinformatics.org.
 Collaborative platforms like Slack, Microsoft Teams, and Google
Workspace facilitate real-time data sharing and collaboration among
researchers.

6. Digital
Resources,
Communication
Technology
Geographic
Information
Systems
Morphological
Algorithms
and
Soft
Computing
ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL TECHNOLOGIES AND
COMPUTATIONAL METHODS
AI
techniques,
Machine
Learning
and
Deep
Learning
 ML techniques are applied to analyze DNA and RNA sequences,
predict gene functions, identify genetic variations, and classify
genetic mutations.
 DL models like Recurrent Neural Networks (RNNs) tasks like
DNA sequence analysis, gene expression prediction, and genome
assembly.

7. Digital
resources,
communication
technology
Geographic
Information
Systems
AI
techniques,
Machine
Learning
and
Deep
Learning
ENHANCING BIOLOGICAL RESEARCH THROUGH DIGITAL TECHNOLOGIES AND
COMPUTATIONAL METHODS
Morphological
Algorithms
and
Soft
Computing
 Morphological Algorithms encouragement in species
identification and population monitoring.
 Soft computing techniques, including Fuzzy Sets, Evolutionary
Algorithms, and others, are crucial in addressing intricate
challenges in bioinformatics and molecular biology, such as
protein classification, drug discovery.

8. THANK FOR THIS OPPORTUNITIES