BIOS 390 UZH HS23 - –Answer "The science that uses the instrument...

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BIOS 390 UZH (HS23)

• Definition of Bioinformatics?

–Answer "The science that uses the instruments of infor- matics to analyze biological data in order to formulate hypotheses about life"

• Tools used by Bioinformatics?

–Answer Software (programming languages, APIs, data- bases, hardware drivers) Hardware (data storage, signal processing, drivers) Algorithms (modelling, encryption)

• 3 Categories of Biological Data?

–Answer Sequence Data (nucleic acids, amino acids) Structural Data (DNA, RNA, proteins) Functional Data (interactions in time and space)

• Types of Databases?

–Answer Primary Database (deposition of original raw data) Derived Database (storing agglomerated and curated data derived from primary sources)

• 3 common file types used in Bioinformatics?

–Answer BAM –Answer Compressed Binary ver- sion of sequence alignemnt map BED –Answer Browser extensible data (\t separated) VCF –Answer Varian Cell Format (standard for derived information, has built-in logic, is very expressive but very complex, and as more rare genetic variants appear, compres- sion becomes less efficient

• Definition and uses of API?

–Answer 1 / 4

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set of routines, protocols, and tools that specifies how software components interact, to exchange data and processing capabilities. Provide Machine Readable responses over HTTP, used for data retrieval and data display.

• What are Ontologies? Why are they useful?

–Answer ontologies in information sciences describe concrete and abstract bjects, their precisely defined hierarchies and rela- tionships.Ontologies in bioinformatics support the move from a descriptive towards an analyt- ical science in describing biological data and relations among it. Good for Queries, easier to search than keywords

• What is not Bioinformatics? Why?

–Answer

• Mathematical Modelling

-Biologically inspired computation -computational & systems biology with an emphasis on modelling Why? Bioinformatics is research, development, or application of computational tools and approaches to make the vast, diverse and complex life sciences data more understandable and useful

• Hypothesis vs data driven science?

–Answer Hypothesis driven –Answer come with a hypothe- sis, study the data using BioInfo to find a proof Data driven –Answer look for patterns, form hypothesis on how these develop, and study that.

• Areas of Bioinformatics?

–Answer -quantitative analysis of -omics -"tree of life" questions 2 / 4

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-image processing for feature extraction -information extraction from prose -functional enrichment of target data

• Definitions of

–Answer

Similarity Sequence Similarity Homology (and subgroups) Analogy –Answer Similarity –Answer The degree to which two items share certain characters.Sequence similarity –Answer two sequences contain a number of identical or related char- acters in corresponding positions.Homology –Answer descended from a shared common ancestor Orthology –Answer derived from common ancestor during speciation (often with retained function) Paralogy –Answer evolved in parallel after gene duplication (often with diverged function) Analogy –Answer similarity without homology, e.g. due to convergent evolution

• What is a Substitution Matrix? Types of Scoring?

–Answer The matrix assigns a value to every possible character pair. The scoring values for all pairs are 3 / 4

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combined to produce a score for the respective alignment.Scoring by Probability –Answer Value = probability that characters in a pair are identical. Alignment score = Product of matrix values of each position of the alignment (ok for identity, not useful for similarity) Arbitrary Score –Answer Value in nucleotide identity = matrix arbitrary score for a matching pair. Alignment score = sum of matrix values of each position of the alignment. (Without normalization, the score will grow with the length of the alignment)

• What is the PAM concept? How to introduce Gap penalties?

–Answer PAM Point Accepted Mutation (or "percent accepted mutation").PAM 1 reflects an evolutionary distance where 1% of characters have been changed –Answer

=> 99% of character pairs of an augment should be identical, 1% mismatched Alignment score = product of matrix values for every pair in the alignment (can weigh Transitions = 3 x Transversions). Can also use LogOdds –Answer add values instead of multiply. Affine gap –Answer high value (A) for gap opening + lower value (B) for every gap elongation step –Answer P = A + nB

• How do BLOSUM matrices work? How do sequence similarities compare to PAM?

–Answer Blosum –Answer BLOck SUbstitution Matrix

BLOSUM 62

–Answer

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