Computational Molecular Microbiology (MBIO 4700) Quiz

Bioinformatics is an interdisciplinary field of science that involves using computer technology to collect, store, analyze, and disseminate biological data and information, such as DNA and amino acid sequences or annotations about those sequences.

Bioinformatics, as related to genetics and genomics, is a scientific subdiscipline that involves using computer technology to collect, store, analyze, and disseminate biological data and information, such as DNA and amino acid sequences or annotations about those sequences.

There are many different definitions of bioinformatics, such as: The retrieval and analysis of biochemical and biological data using mathematics and computer science, as in the study of genomes; The collection, classification, storage, and analysis of biochemical and biological information using computers, especially as applied to molecular genetics and genomics.

Computational molecular microbiology involves the retrieval and analysis of biochemical and biological data using mathematics and computer science, as well as the collection, classification, storage, and analysis of biochemical and biological information using computers, especially as applied to molecular genetics and genomics.

One potential project idea is to start with an alignment, use sequence logos to find conserved features, explore NCBI graphical display, utilize HMMER, use phylogeny to learn about the evolution of the gene/protein sequence, and apply protein (or RNA) folding tools to learn about the product of the gene.

In silico analyses can be viewed and approached as performing a series of experiments, where each 'experiment' may reveal interesting findings about the protein/gene being studied.

Some tools and approaches that can be used to explore a gene or protein include investigating conserved features using sequence logos, utilizing NCBI graphical display, employing HMMER, using phylogeny to study the evolution of the gene/protein sequence, and applying protein (or RNA) folding tools to learn about the product of the gene.

Various analyses can integrate with each other to address questions related to the gene/protein, such as evaluating selection, observing co-evolution of residues within the sequence, and exploring how the analyses collectively contribute to understanding the gene/protein.

Bioinformatics is an interdisciplinary field that uses biology, chemistry, physics, computer science, programming, mathematics, and statistics to analyze and interpret biological data.

Biological data includes DNA, RNA, protein sequences, genome coordinates, biological pathways, and gene expression data.

Types of biological data include characters, strings of characters, integers, floating point numbers, and booleans.

Linear data structures can be linked lists, arrays, or stacks.

Non-linear data structures can be trees or graphs.

Databases are organized collections of structured data, commonly managed by a Database Management System (DBMS).

Biological databases include GenBank, NCBI Protein, UniProt, PDB, NCBI Genome, Ensembl, UCSC, and KEGG.

Bioinformatics tools can be web-based or desktop-based.

Algorithms are well-defined steps for solving a problem and often involve specific data structures.

Bioinformatics algorithms include exhaustive search, greedy algorithms, dynamic programming, divide and conquer, and Hidden Markov Model (HMM).

Markov chains are stochastic processes with the Markov property, while HMM is a more general term for stochastic models with hidden states.

HMM is used to model sequences, such as genes, and can differentiate between different features within a sequence, like introns and exons. HMM uses emission probabilities to assign nucleotides to states and transition probabilities to move between states in a sequence.