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Molecular Biology Lecture > 2: Introduction to Bioinformatics (FINALS) > Flashcards

2: Introduction to Bioinformatics (FINALS) Flashcards

1
Q

→ A field which uses computers to store and analyze molecular biological information

→ It is about finding and interpreting biological data online

→ Marriage between biology and informatics

→ Science of collecting and analyzing complex biological data

A

Bioinformatics

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2
Q

→ A field where biology, mathematics, statistics, computer science, information technology, and other health sciences are merged into a single discipline to process biological data

→ Uses complex machines to read biological data at a much faster rate than before

A

Bioinformatics

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3
Q

What are the 3 principal components of bioinformatics?

A
  1. Creation of Databases
  2. Development of Algorithms and Statistics
  3. The use of these tools for Analysis and Interpretation of various types of biological data
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4
Q

3 Principal Components of Bioinformatics:

→ are like repositories or banks of biologic informations and are designed to collect archive, visualize, and arrange biologic data

→ Allowed the storage and management of large biological data sets

→ Enable scientist to have an intelligent data description, interpretation or retrieval of dat

A

Databases

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5
Q

3 Principal Components of Bioinformatics:

T or F

Data is being generated at a much greater pace than its analysis

A

T

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6
Q

Example of bioinformatics:

→ made in the 1990’s

→objective is to sequence the entire human genome

→ Consist of about 3.2 billion base pairs

→ Finished in 2003

A

Human Genome Project

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7
Q

3 Principal Components of Bioinformatics:

Determine relationships among members of large data sets

A

Development of algorithms and statistics

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8
Q

3 Principal Components of Bioinformatics: Development of algorithms and statistics

Large set of data are organized so relationships can be determined

A

Algorithm

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9
Q

3 Principal Components of Bioinformatics:

A concept under this is biological data

A

The use of these tools for analysis and interpretation of various types of biological data

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10
Q

3 Principal Components of Bioinformatics: The use of these tools for analysis and interpretation of various types of biological data

→ Including DNA, RNA, and protein sequences, protein structures, gene expression profiles, and biochemical pathways

A

Biological data

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11
Q

Sciences that attempt to describe a living organism in terms of “omics”

A

Branches of Bioinformatics

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12
Q

Branches of Bioinformatics:

Involve the description of sequences of entire genome

A

Genomics

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13
Q

Branches of Bioinformatics:

Study of all RNA molecules in a living organism

A

Transcriptomics

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14
Q

Branches of Bioinformatics:

→ Description of the entire complement of proteins in a living organism

→ Entire proteins found in a living organism

→ Study of the Sequence, 3D Structures, and other Properties of all Proteins

A

Proteomics

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15
Q

Branches of Bioinformatics:

→ Pertains to microbes like viruses, fungi, parasites, bacteria

→ Genomes of microorganisms are described within a specific environmental niche?

A

Microbiomics

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16
Q

Branches of Bioinformatics:

→ Involved description of chemical processes involving metabolites

A

Metabolomics

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17
Q

Branches of Bioinformatics:

→ Pertains to microbes like viruses, fungi, parasites, bacteria

→ Genomes of microorganisms are described within a specific environmental niche?

A

Microbiomics

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18
Q

Familiarize the DNA/RNA Bioinformatics Applications

A
  1. Retrieving DNA sequences from databases
  2. Computing nucleotide compositions
    Identifying restriction sites
  3. Designing polymerase-chain reaction (PCR) primers
  4. Identifying open reading frames (ORF)
  5. Finding repeats
  6. Computing the optimal alignment between 2 or more DNA sequences
  7. Finding polymorphic sites in genes (SNPs)
  8. Assembling sequence fragments
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19
Q

Familiarize other applications in bioinformatics given

A
  1. Sequence alignment and analysis
  2. Mapping and analyzing DNA, RNA, Protein, Amino acid, and Lipid sequences
  3. Creation and Visualization of 3D structure models for biological molecules of significance
  4. Genome annotation
  5. Genetic diseases
  6. Designer medicine
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20
Q

Familiarize Applications in Various Fields

A

tignan niyo nlng sa ppt to huhuhu

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21
Q

Why do we use Bioninformatics?

A

Saves time when doing real experiment

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22
Q

Importance of Bioinformatics:

T or F

Study should end by simulated experiment on computer instead of a real environment

A

F (Study might START by simulated experiment on computer instead of a real environment)

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23
Q

Importance of Bioinformatics: Identify the process

Simulated experiment on computer = ?

Primer optimized and used in amplification reaction =

A

Simulated experiment on computer = In Silico

Primer optimized and used in amplification reaction = Wet Lab

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24
Q

Importance of Bioinformatics: Identify whether “In Silico” or “Wet Lab”

Target Identification

A

In Silico

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25
Q

Importance of Bioinformatics: Identify whether “In Silico” or “Wet Lab”

Primer Characterization

A

Wet lab

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26
Q

Importance of Bioinformatics: Identify whether “In Silico” or “Wet Lab”

Assay Optimization

A

Wet lab

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27
Q

DNA/RNA Bioinformatics Applications:

→ sequence with start codon (AUG), until a stop codon UAG, UGA, UAA

→ predicting elements of DNA/RNA secondary structure

A

open reading frames (ORF)

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28
Q

Three earliest DNA Sequences and Protein Databases?

A
  1. Nucleic acids
  2. Protein
  3. Other databases?
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29
Q

Three earliest DNA Sequences and Protein Databases:

What is the database for Nucleic acids

A

International Nucleotide Sequence Database

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30
Q

Three earliest DNA Sequences and Protein Databases:

Composition of International Nucleotide Sequence Database

A
  1. DDBJ (DNA DataBank of Japan)
  2. EMBL (European Molecular Biology Lab)
  3. GenBank (USA)
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31
Q

Three earliest DNA Sequences and Protein Databases:

What is the database for Protein?

A

Worldwide Protein Data Bank

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32
Q

Three earliest DNA Sequences and Protein Databases:

Familiarize the other databases

A
  1. Ensembl
  2. Human metabolome Database
  3. Gene Expression Databases
  4. Phenotypic Database
  5. RNA Databases
  6. Amino acid/protein Databases
  7. RNA Databases
  8. Protein-Protein and other Molecular Interactions
  9. Signal Transduction Pathway Databases
  10. Bacterial DNA Databases
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33
Q

T or F

In Gene Analysis Application, changes the sequence of the gene binge expressed always result to normal and healthy person

A

F (A DISEASE MAY ARISE due to changes the sequence of the gene binge expressed)

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34
Q

Gene Analysis Application

T or F

Sickle cell anemia results from point mutation of tyrosine to valine in beta-acid chain

A

F (substitution of GLUTAMIC ACID to VALINE)

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35
Q

This refers to genetic characteristics

A

Genotype

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36
Q

This refers to Physical Characteristics

A

Phenotype

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37
Q

Gene Analysis Application:

→ leads to sickle cell anemia
→ A recessive trait

A

Single Nucleotide mutation

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38
Q

Gene Analysis Application: Single Nucleotide mutation

Normal Sequence: G-A-G (Glutamic Acid)
Mutated: G-U-G (Valine)

Which amino acid became mutated?

A

A

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39
Q

Gene Analysis Application: Single Nucleotide mutation

If the Father and Mother are Heterozygous for sickle cell gene, how many are:

a. children who will manifest the disease

b. normal children

c. children who are carriers

A

a. ¼ of children develop sickle cell disease

b. ¼ are normal

c. ½ are carriers

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40
Q

What are the 2 Bioinformatic Actvities?

A
  1. Finding DNA/Protein Sequence
  2. Sequence Alignment
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41
Q

To find gene or protein sequences online, what websites should be used?

A
  1. Genbank
  2. Protein Data Bank
42
Q

To find gene sequences online, what website should be used?

43
Q

To find protein sequences online, what website should be used?

A

Protein Data Bank

44
Q

→ A way of rearranging sequences of DNA, RNA, or protein to identify regions of similarity

A

Sequence Alignment

45
Q

Sequence Alignment:

What are the 2 factors involved where sequence alignment is made

A

Reference and Unknown Sequence

46
Q

Sequence Alignment:

Reference sequence is also known as what?

A

Known, Subject sequence

47
Q

Sequence Alignment:

Unknown sequence is also known as?

A

Query sequence

48
Q

Sequence Alignment:

Familiarize Importance of identifying regions of similarity

A
  1. To understand functional, structural or evolutionary relationships between the sequences
  2. help identify dissimilar regions of the DNA sequence useful for designing primers
49
Q

Sequence Alignment: Familiarize Importance of identifying regions of similarity

If sequences are similar, what does it mean?

A

they have similar functions or structure

50
Q

Sequence Alignment: Familiarize Importance of identifying regions of similarity

Can either mean belonging to the same group or distant relationship

A

Evolutionary relationship

51
Q

Sequence Alignment: Familiarize Importance of identifying regions of similarity

T or F

Identifying similar regions of DNA sequence is useful for designing primers

A

F (Identifying DISSIMILAR REGIONS of DNA sequence is useful for designing primers)

52
Q

2 Types of Sequence Alignment

A
  1. Pairwise
  2. Multiple
53
Q

Types of Sequence Alignment:

Compare two sequences

54
Q

Types of Sequence Alignment:

Compare more than two sequences

55
Q

What are the websites used in pairwise sequence alignment?

A
  1. EMBOSS WATER
  2. BLAST
56
Q

What are the websites used in multiple sequence alignment?

A
  1. MUSCLE
  2. MAFFT
  3. CLUSTAL Omega
57
Q

What are the Types of Pairwise Sequence Alignments?

A
  1. Global alignment
  2. Local alignment
58
Q

Types of Pairwise Sequence Alignments

→ Matching the residues (bases or amino acids) of two sequences across their entire length

→ The whole of DNA is aligned

A

Global Alignment

59
Q

3 Types of Pairwise Sequence Alignments

→ Matching of two sequences from regions which have more similarity with each other

→ The two sequences may or may not be related

→ to see whether a substring (a part) in one sequence aligned well with substring (a part) in other sequence

A

Local alignment

60
Q

Sequence Alignments

→ There multiple sequences being aligned

→ The residues are colored that differences can easily be seen

A

Multiple Sequence alignment: Clustal Omega

61
Q

What type of Pairwise Sequence Alignments is appropriate for the given application:

Comparing two genes or proteins with the same function

A

Global Alignment

62
Q

What type of Pairwise Sequence Alignments is appropriate for the given application:

Searching for local similarities in large sequences

A

Local alignment

63
Q

What type of Pairwise Sequence Alignments is appropriate for the given application:

Looking for conserved domains of motifs in two proteins

A

Local Alignment

64
Q

What type Sequence Alignments is appropriate for the given application:

Determines if all of the sequences are identical by presence of ASTERISK

A

Multiple Sequence alignment: Clustal Omega

65
Q

T or F

In Multiple Sequence alignment: Clustal Omega, absence if asterisk means the sequence is similar

A

F (absence of asterisk means sequence is DISSIMILAR/VARIATION)

66
Q

Pairwise Sequence Alignment: Emboss Water

Straight line indicates that the sequences are?

67
Q

Pairwise Sequence Alignment: Emboss Water

Straight line indicates that the sequences are?

68
Q

Pairwise Sequence Alignment: Emboss Water

Dot/period indicates that the sequences are?

A

Dissimilar

69
Q

Pairwise Sequence Alignment: Emboss Water

Meaning of Y in the sequence?

A

Any pyrimidine

70
Q

Pairwise Sequence Alignment: Emboss Water

Meaning of R in the sequence?

A

Any purine

71
Q

Pairwise Sequence Alignment: Emboss Water

Meaning of N Ain the sequence?

72
Q

Pairwise Sequence Alignment: Website

→ Finds regions of local similarity between sequences

→ The amino acid sequences of proteins or nucleotide of DNA sequences

→ Compare a query sequence with a library or database of sequence

→ Identify library sequences that resemble the query sequence above certain threshold

→ To Identify uncharacterized genes

A

Basic Local Alignment Search Tool (BLAST)

73
Q

Query, Database, Remarks of the program BLASTn?

A

Query: Nucleotide
Database: Nucleotide
Remarks: for high scoring matches

74
Q

Query, Database, Remarks of the program BLASTp?

A

Query: Protein
Database: Protein
Remarks: uses substitution matrices

75
Q

Query, Database, Remarks of the program BLASTx?

A

Query: Nucleotide (trans)
Database: Protein
Remarks: for novel DNA seqs and EST analysis

76
Q

Query, Database, Remarks of the program TBLASTx?

A

Query: Protein
Database: Nucleotide
Remarks: for STS and EST assignments in databases

77
Q

What are the 2 possible results of BLAST?

A
  1. Graphic Summary
  2. Sequences producing significant alignment
78
Q

supply multiple sequences to be aligned to identity regions of similarity that may be a consequence of functional, structural, or evolutionary relationships

what program

A

Multiple Sequence Comparison by Log Expectation (MUSCLE)

79
Q

Multiple Sequence Comparison by Log Expectation (MUSCLE):

T or F

Each sequence should have definition line preceded by the”>” greater than symbol

80
Q

Multiple Sequence Comparison by Log Expectation (MUSCLE):

T or F

Choose part of sequence that is similar for primer

A

F (DO NOT choose part of sequences that is similar; dapat di sila similar bb)

81
Q

What appropriate alignment sequence should be used? what website?

Aligning the envelope genes of the 4 dengue virus

A

Multiple Alignment Sequence: MUSCLE

82
Q

BLAST or Multiple alignment

You supply one or more query sequences

83
Q

BLAST or Multiple alignment

Compares nucleotide or protein sequences to sequence databases

84
Q

BLAST or Multiple alignment

Uses to infer functional and evolutionary relationships between sequences

A

BLAST

parangboth

85
Q

BLAST or Multiple alignment

Uses to infer functional and evolutionary relationships between sequences

A

BLAST (both dapat)

86
Q

BLAST or Multiple alignment

Help identify members of gene families

87
Q

BLAST or Multiple alignment

You supply multiple sequences to be aligned to identity regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences

A

Multiple alignment

88
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

→ a text-based, bioinformatic data format used to store nucleotide or amino acid sequences (e.g. Deoxyribonucleic Acid [DNA] or Ribonucleic Acid [RNA]).

→ pronounced “Fast A” (“fast-aye”) because the name is a shortening of “FAST-All”.

89
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

Can be present in one of the sequences wherein one or more amino acid residues have been deleted from the sequence

90
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

The input sequence that is being compared to others in the database aka sequence of interest

A

Query Sequence

91
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

The sequence you are comparing to

A

Subject Sequence

93
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

A diagram that depicts the lines of evolutionary descent of different species, organisms, or genes from a common ancestor

A

Phylogenetic tree

94
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

A series of digits that are assigned consecutively to each sequence record processed by NCBI

95
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

A unique identifier assigned to a record in sequence databases such as GenBank

A

Accession number

96
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

The process of deriving the structural and functional information of a protein or gene from a raw data set using different analysis, comparison, estimation, precision, and other mining techniques

A

Genome annotation

97
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

→ A set of values for qualifying the set of one residue being substituted by another in an alignment

→ Calculated by adding substitution scores, defined for each aligned pair of letters, and gap scores for each run of letters in one segment aligned with null characters inserted into the other

98
Q

DEFINITION OF TERMS IN BIO INFORMATICS:

A parameter that describes the number of hits one can “expect” to see by chance when searching a database of a particular size

A

Expect Value

99
Q

Full name of BLAST?

A

Basic Local Alignment Search Tool

100
Q

Full name of MUSCLE?

A

Multiple Sequence Comparison by Log Expectation

Molecular Biology Lecture (17 decks)

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