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molbio > Bioinformatics lecture > Flashcards

Bioinformatics lecture Flashcards

1
Q

The extent to which two sequences are the same

A

Identity

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2
Q

Lining up two or more sequences to search for the maximal regions of identity in order to assess the extent of biological relatedness of homology

A

Alignment

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3
Q

The relatedness of sequences

A

Similarity

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4
Q

A fixed set of commands in a computer program

A

Algorithm

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5
Q

A space introduced in alignment to compensate for insertions or deletions in one of the sequences being
compared

A

Gap

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6
Q

Similarity attributed to descent from a common ancestor

A

Homology

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7
Q

The sequence presented for comparison with all other sequences in a selected database.

A

Query

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8
Q

The genetic sequence database sponsored by the National Institutes of Health.

A

GenBank

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9
Q

describes the number of matches
to the query by chance when searching a database of a
particular size.

A

E- value (Expect value)

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10
Q

study on evolutionary relatedness among species by comparing homologies and differences in gene
sequences

A

Phylogenetics

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11
Q
  • A field which uses computers to store and analyze
    molecular biological information.
  • application of tools of computation and analysis to the capture and interpretation of biological data.
A

BIOINFORMATICS

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12
Q
  • Allow the storage and management of large biological data sets
  • Data is being generated at a much greater pace than its
    analysis (Human Genome Project)
A

CREATIO OF DATABASES

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13
Q

Determine relationships among members of large data users

A

DEVELOPMENT OF ALGORITHMS AND STATISTICS

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14
Q
  • Transcriptomics
  • Microbiomics
  • Metabolomics
  • Genomics
  • Proteomics
A

BRANCHES OF BIOINFORMATICS

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15
Q
  • Retrieving DNA sequences from databases
  • Computing nucleotide compositions
  • Identifying restriction sites
  • Designing polymerase chain reaction (PCR) primers
  • Identifying open reading frames (ORFs)
  • Predicting elements of DNA/RNA secondary structure
  • Finding repeats
  • Computing the optimal alignment between two or more DNA
    sequences
  • Finding polymorphic sites in genes (single nucleotide
    polymorphisms, SNPs)
  • Assembling sequence fragments
  • Creation and visualization of 3D structure models for
    biological molecules of significance.
A

BIOINFORMATICS APPLICATIONS

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16
Q
  • Microbial genome applications
  • Molecular medicine
  • Personalized medicine
  • Gene therapy
  • Drug development
  • Antibiotic resistance
  • Evolutionary studies
  • Waste cleanup
  • Biotechnology
  • Climate change studies
  • Alternative energy sources
  • Crop improvement
  • Forensic analysis
  • Bio-weapon creation
  • Insect resistance
  • Improve nutritional quality
  • Veterinary science
A

BIOINFORMATICS APPLICATIONS IN VARIOUS FIELDS

17
Q

THREE EARLIEST DNA SEQUENCE AND PROTEIN DATABASES

A
  • DDBJ (DNA DataBank of Japan)
  • EMBL (European Molecular Biology Lab)
  • Genbank (USA)
18
Q
  • Contain original data in the form of primary sequence data
    or structural data as submitted by the scientific community.
  • Examples: GenBank, EMBL, DDBJ, SWISS-PROT and PIR
A

PRIMARY DATABASES

19
Q

Contain information that has been
process and derived from the raw data available in primary
database

A

SECONDARY DATABASES

20
Q
  • A way of rearranging sequences of DNA, RNA or protein to identify regions of similarity.
A

SEQUENCE ALIGNMENT

21
Q

To understand functional, structural, or
evolutionary relationships between the sequences

A

identify regions of similarity

22
Q

TYPES OF SEQUENCE ALIGNMENT

A
  • Pairwise - compare two sequences
  • Multiple- compare more than two sequences
23
Q

compare more than two sequences
o MUSCLE
o MAFFT
o CLUSTAL Omega

A

Multiple

24
Q

compare two sequences
o EMBOSS WATER
o BLAST

A

Pairwise

25
Q

Matching the residues (bases or amino
acids) of two sequences across their entire length
o matches the identical sequences
o The two sequences are treated as potentially
equivalent

A

Global alignment

26
Q

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

o The two sequences may or may not be related
o Purpose
▪ To see whether a substring (a part) in one
sequence aligns well with a substring (a
part) in the other sequence
o Applications:
▪ Searching for local similarities in large
sequences (e.g., newly sequenced
genomes)
▪ Looking for conserved domains of motifs
in two proteins

A

Local alignment

27
Q

multiple sequence alignment tool
that arranges the sequences of DNA, RNA or protein to identify regions of similarity

A

MUSCLE

28
Q
  • finds regions of local similarity between sequences.
  • the amino acid sequences of proteins or the nucleotides of
    DNA sequences.
  • compare a query sequence with a library or database of
    sequences, and identify library sequences that resemble the
    query sequence above a certain threshold.
  • can be used to infer functional and evolutionary
    relationships between sequences as well as help identify
    members of gene families.
A
  • BLAST
    BASIC LOCAL ALIGNMENT SEARCH TOOL (BLAST)
29
Q
  • In BLAST
    o you supply one or more query sequences and it
    compares nucleotide or protein sequences to
    sequence databases
  • In a multiple alignment
    o you supply multiple sequences to be aligned to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences
A

BLAST DIFFER FROM MULTIPLE SEQUENCE ALIGNMENT

30
Q

you supply one or more query sequences and it compares nucleotide or protein sequences to
sequence databases

A

BLAST

31
Q

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

A

multiple alignment

molbio (17 decks)

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