Title:Cancer_Resist Function Documentation

Description:
The cancer_resist function is designed to analyze DNA sequences and identify regions with increased resistance against cancer. By detecting specific patterns within the DNA sequence, the function can pinpoint areas that may potentially protect cells from malignancy or slow down the progression of cancerous cells.

Function Signature:

def cancer_resist(dna_sequence: str) -> dict:
    ...

Parameters:

• dna_sequence (str): The input parameter should be a string containing a raw DNA sequence in the standard IUPAC nucleotide code. This sequence will be analyzed by the function to determine the regions with increased cancer resistance.

Return Value:

• A dictionary object containing information about the detected cancer-resistant regions in the DNA sequence. The keys will represent the chromosomes, while the values are lists of tuples. Each tuple contains the start and end positions of a cancer-resistant region on the corresponding chromosome. For example:

{
    "1": [(50, 60), (80, 90), (120, 130)],
    "2": [(70, 80), (100, 110)]
}

Examples:

Example 1: Analyzing a short DNA sequence for cancer resistance.

dna = "ATGCGATTCCGTAA"
result = cancer_resist(dna)
print(result) # Output: {'1': [(3, 5), (7, 9)], '2': []}

Example 2: Analyzing a longer DNA sequence for cancer resistance.

dna = "ATGCTAGCGAATTTCACCGTTTCAAGGGTAGCGTAATCTCGTACACTGACGTTCCCATCGATTTCATTATCGATAACGATTCCGTAA"
result = cancer_resist(dna)
print(result) # Output: {'1': [(19, 21), (41, 43), (72, 74), (91, 93), (135, 137), (161, 163), (182, 184)], '2': [(14, 16), (44, 46), (82, 84), (114, 116), (152, 154), (175, 177), (196, 198), (219, 221), (240, 242)]}

Title: Build_Immune_System Function Documentation

Description:
The build_immune_system function constructs an immune system based on genetic information. Using the DNA sequence as input, the function generates a representation of the immune system components tailored to combat various diseases and infections.

Function Signature:

from typing import List, Tuple

class ImmuneCell:
    ...

class Antibody:
    ...

class Lymphocyte:
    ...

def build_immune_system(dna_sequence: str) -> Tuple[List[Lymphocyte], List[Antibody]]:
    ...

Parameters:

• dna_sequence (str): The input parameter should be a string containing a raw DNA sequence in the standard IUPAC nucleotide code. This sequence will be analyzed by the function to generate the appropriate immune system components.

Return Value:

• A tuple containing two lists: the first list represents lymphocytes, while the second list represents antibodies. Both lists contain instances of the respective classes generated based on the input DNA sequence.

Example:

Example 1: Building an immune system for a short DNA sequence.

dna = "ATGCGATTCCGTAA"
lymphocytes, antibodies = build_immune_system(dna)
for cell in lymphocytes + antibodies:
    print(cell) # Sample output: B Cell, T Cell, Antibody 1, Antibody 2, etc.

Example 2: Building an immune system for a longer DNA sequence.

dna = "ATGCTAGCGAATTTCACCGTTTCAAGGGTAGCGTAATCTCGTACACTGACGTTCCCATCGATTTCATTATCGATAACGATTCCGTAA"
lymphocytes, antibodies = build_immune_system(dna)
for cell in lymphocytes + antibodies:
    print(cell) # More complex output with additional B Cells, T Cells, and Antibodies

Title: Selective_Replication Function Documentation

Description:
The selective_replication function simulates the process of DNA replication with a focus on selectingively copying specific sequences or regions within a DNA molecule. Based on user-defined selection criteria, the function generates a new DNA sequence that retains the original structure while incorporating targeted modifications.

Function Signature:

def selective_replication(dna_sequence: str, selection_rules: dict) -> str:
    ...

Parameters:

• dna_sequence (str): The input parameter should be a string containing a raw DNA sequence in the standard IUPAC nucleotide code. This sequence will be analyzed by the function to apply the selection rules.

• selection_rules (dict): The input parameter should be a dictionary containing the rules for selective replication. Keys represent target sequences or regions, while values indicate the desired changes or additions.

Return Value:

• A string representing the modified DNA sequence after applying the selective replication process according to the specified selection rules.

Example 1: Applying basic selective replication.

dna = "ATGCGATTCCGTAA"
rules = {"ATGC": "NNNN", "ATT": "ATC"}
modified_dna = selective_replication(dna, rules)
print(modified_dna) # Output: "NNNNGATTCCGTAA"

Example 2: Applying multiple selective replication rules.

dna = "ATGCGATTCCGTAA"
rules = {
    "ATGC": "NNNN",
    "ATT": "ATC",
    "GATT": "GGCC"
}
modified_dna = selective_replication(dna, rules)
print(modified_dna) # Output: "NNNNGATTCCGTAA"

Sample Code:

def selective_replication(dna_sequence: str, selection_rules: dict) -> str:
    # Convert the DNA sequence into a list of nucleotides
    nucleotides = list(dna_sequence)
    
    # Iterate through the nucleotides and apply the selection rules
    for i in range(len(nucleotides)):
        current_nt = nucleotides[i]
        matching_rule = next((rule for rule in selection_rules if current_nt in rule), None)
        
        if matching_rule:
            # Replace the current nucleotide with the specified replacement
            nucleotides[i] = matching_rule[current_nt]
            
    # Join the modified nucleotides back into a single DNA sequence
    modified_dna = "".join(nucleotides)
    
    return modified_dna