This assignment covers both the theoretical and practical aspects of this course. The marking rubrics are heavily based on data & information management. Later assignment will focus more on...

This assignment covers both the theoretical and practical aspects of this course. The marking rubrics are heavily based on data & information management. Later assignment will focus more on abstraction & design. You will investigate the impact of having different data structures and algorithms to solve a given task. Java is the only acceptable language for this assignment. This assessment covers the following course learning outcomes: CLO 1 – Evaluate the efficiency of algorithms. CLO 2 – Assess the suitability of different algorithms for solving a given problem. In this assignment, you will be making your first dummy search engine where you will analyze its efficiency empirically. Making a complete Biological Database Search Engine is a complicated task as it has a lot of ingredients including high-end servers and data mining tools. You are required to make a mini biological search engine only for one dataset of Proteins from the Protein Data Bank (available in Kaggle at https://www.kaggle.com/shahir/protein-dataset/version/1?select=pdb_data_no_dups.csv). You will be using a simplified version of the dataset available on Moodle as proteins.csv. 1. Your first task is to read this data in your Java program and store it in the following built-in data structures: a. Hashtable b. LinkedList c. ArrayList 2. Next, use the following generic search algorithms to test the search capability for your dataset based on all the data structures used above: a. Sequential Search for ArrayList and LinkedList. b. Built-in Binary Search for ArrayList and LinkedList. c. Built-in HashTable Search for the Hashtable. All the above algorithms should be able to search for a protein (structureId) from the dataset. In the future, more datasets would be added so the algorithm used should be generic enough to cater for any given user-defined data type.