Transfer over omics

content/_index.md

@@ -23,7 +23,6 @@ Yet, generational barriers outside of an individual's influence hinder a person'
 Breadcrumbs represents [OASCI's](https://www.oasci.org/) initiative to fundamentally transform access to educational materials, embodying the spirit of discovery and the sharing of knowledge fragments that have traditionally been accessible only through the goodwill of others.
 Breadcrumb websites are freely accessible resources, and we encourage contributions, improvements, and adaptations so long as they abide by the terms outlined in the [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license.
 
-
 ## License
 
 Code contained in this project is released under the [MIT License](https://spdx.org/licenses/MIT.html) as specified in [`LICENSE_CODE`](https://github.com/oasci-bc/omics/blob/main/LICENSE_CODE.md).

content/alignment/_index.md

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+---
+title: Sequence alignment
+type: docs
+---
+
+
+In bioinformatics, a sequence alignment is a way of arranging two or more sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between them.
+In many cases, the input set of query sequences are assumed to have an evolutionary relationship by which they share a linkage and are descended from a common ancestor.
+Aligned nucleotide or amino acid residue sequences are typically represented as rows within a matrix.
+Gaps are inserted between the residues to align identical or similar characters in columns.
+A pairwise alignment aligns two sequences, while a multiple sequence alignment (MSA) aligns three or more.
+
+
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/b/b5/Histone_Alignment.png)
+> 
+> 
+> A multiple sequence alignment of mammalian histone proteins.
+> Sequences are the amino acids for residues 120-180 of the proteins.
+> Residues that are **conserved** across all sequences are highlighted in grey.
+> Below the protein sequences is a key denoting conserved sequence (*), conservative mutations (:), semi-conservative mutations (.), and non-conservative mutations ( ).
+> Conservative mutations produce chemically similar amino acids, while non-conservative mutations result in chemically distant residues.
+> 
+> Credit: [Wikipedia](https://upload.wikimedia.org/wikipedia/commons/b/b5/Histone_Alignment.png).
+
+## Homology
+
+In biology, homology is similar due to shared ancestry between structures or genes in different taxa.
+A typical anatomical example of homologous structures is the forelimbs of vertebrates, where the wings of bats and birds, the arms of primates, the front flippers of whales, and the forelegs of four-legged vertebrates like dogs and crocodiles are all derived from the same ancestral tetrapod structure.
+Evolutionary biology explains homologous structures adapted to different purposes due to descent with modification from a common ancestor.
+
+Sequence homology between protein or DNA sequences is similarly defined in terms of shared ancestry.
+Two segments of DNA can have shared ancestry because of either a speciation event or a gene duplication event.
+Homology among proteins or DNA is inferred from their sequence similarity.
+Significant similarity proves that two sequences are related by divergent evolution from a common ancestor.
+Alignments of multiple sequences are used to discover homologous regions.
+
+### Interpretation
+
+Suppose two sequences in an alignment share a common ancestor.
+In that case, mismatches can be interpreted as point mutations and gaps as indels (insertion or deletion mutations) introduced in one or both lineages in the time since they diverged from one another.
+In protein sequence alignments, the degree of similarity between amino acids occupying a particular position in the sequence can be interpreted as a rough measure of how conserved a particular region is among lineages.
+The absence of substitutions, or the presence of only very conservative mutations (that is, the substitution of amino acids whose side chains have similar biochemical properties) in a particular region of the sequence, suggests that this region has structural or functional importance.
+
+### Conserved sequences
+
+In evolutionary biology, conserved sequences are identical or similar in nucleic acids (DNA and RNA) or proteins across species, within a genome, or between donor and receptor taxa.
+Conservation indicates that a sequence has been maintained by natural selection, likely because mutations in the sequence dramatically harm the organism's health and fitness.
+
+A highly conserved sequence has remained relatively unchanged far back up the phylogenetic tree and far back in geological time.
+Examples of highly conserved sequences include the RNA components of ribosomes, which are present in all domains of life, the homeobox sequences widespread among eukaryotes, and the tmRNA in bacteria.
+The study of sequence conservation overlaps with the fields of genomics, proteomics, evolutionary biology, phylogenetics, bioinformatics, and mathematics.
+
+Just because two sequences are similar does not mean that the sequence has been conserved and the sequences are homologs.
+Convergent evolution can result in two unrelated sequences becoming similar.
+In some cases, two sequences can code for proteins or parts of proteins with similar functions but with no shared evolutionary history.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/9/94/Caspase-motif-alignment.png)
+> 
+> MSA of the seven Drosophila caspases colored by motifs.
+> Note the long stretches of gaps (-) required to align the sequences.
+
+### Global and local alignments
+
+Global alignments, which attempt to align every residue in every sequence, are most valuable when the sequences in a set are similar and of roughly equal size.
+(This does not mean global alignments cannot start and/or end in gaps.)
+Local alignments are more useful for dissimilar sequences suspected to contain relatively small regions of similarity or similar sequence motifs within their larger sequence context.
+
+## Multiple sequence alignment
+
+Multiple sequence alignment extends pairwise alignment to incorporate more than two sequences simultaneously.
+Multiple alignment methods try to align all sequences in a given query set.
+Multiple alignments are often used in identifying conserved sequence regions across a group of sequences hypothesized to be evolutionarily related.
+Such conserved sequence motifs can be used in conjunction with structural and mechanistic information to locate enzymes' catalytic active sites.
+Alignments are also used to establish evolutionary relationships by constructing phylogenetic trees.
+Multiple sequence alignment is often used to assess sequence conservation of protein domains, tertiary and secondary structures, and even functionally significant individual amino acids or nucleotides.
+
+Multiple sequence alignment also refers to aligning a set of sequences.
+MSAs require more sophisticated methodologies than pairwise alignment because they are more computationally complex.
+Multiple sequence alignments are computationally tricky, one of the original challenges tackled by computational biologists.
+The utility of these alignments in bioinformatics has led to the development of various methods suitable for aligning three or more sequences.
+
+### Consensus sequences
+
+MSAs allow the determination of a consensus sequence.
+In molecular biology and bioinformatics, the consensus sequence (or canonical sequence) is the calculated sequence of most frequent residues, either nucleotide or amino acid, found at each position in a sequence alignment.
+Consensus sequences are often printed at the bottom of MSAs and can be elaborated on using sequence logos (see below).
+Developing software for pattern recognition is a significant topic in genetics, molecular biology, and bioinformatics.
+Specific sequence motifs can function as regulatory sequences controlling biosynthesis or signal sequences directing a molecule to a specific site within the cell or regulating its maturation.
+Since these sequences have an essential regulatory function, they are thought to be conserved across long periods of evolution.
+In some cases, evolutionary relatedness can be estimated by the amount of conservation of these sites.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/b/b4/Hemagglutinin-alignments.png)
+> 
+> MSA of 27 avian influenza hemagglutinin protein sequences colored by residue conservation (top) and residue properties (bottom).
+
+### Phylogenetic use
+
+Multiple sequence alignments can be used to create a phylogenetic treeLinks to an external site.
+This is made possible by two reasons.
+The first is that functional domains known in annotated sequences can be used for alignment in non-annotated sequences.
+The other is that conserved regions known to be functionally important can be found.
+This makes it possible to use multiple sequence alignments to analyze and find evolutionary relationships through homology between sequences.
+Point mutations and insertion or deletion events (called indels) can be detected.
+
+By locating conserved domains, multiple sequence alignments can also be used to identify functionally important sites, such as binding sites, active sites, or sites corresponding to other key functions.
+When looking at multiple sequence alignments, it is useful to consider different aspects of the sequences when comparing sequences.
+These aspects include identity, similarity, and homology.
+Identity means that the sequences have identical residues at their respective positions.
+On the other hand, similarity has to do with the sequences being compared having similar residues quantitatively.
+For example, in terms of nucleotide sequences, pyrimidines and purines are considered similar.
+Similarity ultimately leads to homology in that the more similar sequences are, the closer they are to being homologous.
+This similarity in sequences can then go on to help find common ancestry.
+
+### Gallery
+
+Below are examples of MSAs.
+Try to determine what the color coding indicates, how highly conserved regions are with the alignments, and if a consensus sequence is shown.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/7/79/RPLP0_90_ClustalW_aln.gif)
+> 
+> First 90 positions of a protein multiple sequence alignment of instances of the acidic ribosomal protein P0 (L10E) from several organisms.
+> Generated with ClustalX.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/a/a7/WPP_domain_alignment.PNG)
+> 
+> TODO:
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/thumb/9/98/Muscle_alignment_view.png/1600px-Muscle_alignment_view.png)
+> 
+> These are sequences being compared in a MUSCLE multiple sequence alignment (MSA).
+> The sequence names (leftmost column) are from various louse species, while the sequences themselves are in the second column.
+> Note the large insertion present in a single sequence.
+
+## Sequence logos
+
+In bioinformatics, a sequence logo represents the sequence similarity of nucleotides (in a strand of DNA/RNA) or amino acids (in protein sequences).
+A sequence logo is created from a collection of aligned sequences.
+It depicts the consensus sequence and diversity of the sequences.
+Sequence logos are frequently used to depict sequence characteristics such as protein-binding sites in DNA or functional units in proteins.
+
+A sequence logo consists of a stack of letters at each position, though sometimes one letter is much larger than the others.
+The relative sizes of the letters indicate their frequency in the sequences.
+The total height of the letters depicts the information content of the position, with more informative positions giving researchers more confidence in conclusions about a position in the logo.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/b/bf/KozakConsensus.jpg)
+> 
+>  A sequence logo showing the most conserved bases around the initiation codon from all human mRNAs (Kozak consensus sequence).
+> Note that the initiation codon is not drawn to scale.
+
+### Sequence motif
+
+The similarity in a sequence alignment or sequence logo may be due to relatively recent common ancestry or similar molecular function.
+Functionally similar sequences are termed sequence motifs.
+A sequence motif is a nucleotide or amino-acid sequence pattern that is widespread and usually assumed to be related to the biological function of the macromolecule.
+
+### Consensus logo
+
+A consensus logo is a simplified variation of a sequence logo.
+A consensus logo is created from a collection of aligned protein or DNA/RNA sequences like a sequence logo.
+It conveys information about the conservation of each position of a sequence motif or sequence alignment.
+However, a consensus logo displays only conservation information and not explicitly the frequency information of each nucleotide or amino acid at each position.
+Instead of a stack made of several characters, denoting the relative frequency of each character, the consensus logo depicts the degree of conservation of each position using the height of the consensus character at that position.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/8/85/LexA_gram_positive_bacteria_sequence_logo.png)
+> 
+> A consensus logo for the LexA-binding motif of several Gram-positive species.
+
+## Acknowledgements
+
+Some of this material was adapted with permission from the following sources:
+
+-   [Sequence alignment](https://en.wikipedia.org/wiki/Sequence_alignment)
+-   [Multiple sequence alignment](https://en.wikipedia.org/wiki/Multiple_sequence_alignment)
+-   [Homology](https://en.wikipedia.org/wiki/Homology_(biology))
+-   [Consensus sequence](https://en.wikipedia.org/wiki/Consensus_sequence)
+-   [Sequence Logos](https://en.wikipedia.org/wiki/Sequence_logo)

content/alignment/dotplot/_index.md

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+---
+title: Dot plot
+type: docs
+weight: 1
+---
+
+
+A dot plot is a graphical method used in bioinformatics to compare two biological sequences, revealing their similarity and differences at a glance.
+This technique plots one sequence along the x-axis and the other along the y-axis of a two-dimensional matrix.
+Points, or "dots," are marked on this matrix wherever the elements (nucleotides in DNA/RNA or amino acids in proteins) from one sequence match those from the other sequence based on a predefined criterion.
+It serves as a preliminary step in sequence analysis, helping researchers visualize alignments, repetitions, inversions, and regions of conservation without the computational complexity of more advanced alignment algorithms.
+
+> ![](https://upload.wikimedia.org/wikipedia/commons/3/33/Zinc-finger-dot-plot.png)
+> 
+> This is a DNA dot plot of a human zinc finger transcription factor (GenBank ID NM_002383) showing regional self-similarity.
+> The main diagonal represents the sequence's alignment with itself; lines off the main diagonal represent similar or repetitive patterns within the sequence.
+> 
+> Credit: [Wikipedia](https://en.wikipedia.org/wiki/Dot_plot_%28bioinformatics%29)
+
+## Interpretation
+
+When analyzing a dot plot for sequence alignment, you start at the upper left corner, marking the beginning of both sequences being compared.
+This point is crucial as it signifies the commencement of the analysis.
+Conversely, the path concludes at the lower right corner, which denotes the endpoint of both sequences, encapsulating the entire comparison within the confines of the plot.
+The path through the dot plot is navigated via three principal directions:
+
+-   eastward (right) along the x-axis, which indicates progression in the x-axis sequence without a corresponding match in the y-axis sequence, suggesting a gap or insertion in the sequence represented on the y-axis;
+-   southward (down) along the y-axis, which signifies advancement in the y-axis sequence without a matching element in the x-axis sequence, hinting at a gap or insertion in the x-axis sequence;
+-   and southeastward (diagonally down and right), which denotes a matching pair of elements, thus advancing both sequences in unison.
+
+Interpreting alignments within this framework, any path that adheres strictly to these three directions from the plot's upper left to its lower right corner symbolizes a potential alignment between the two sequences.
+This path methodically delineates through regions of matches (diagonal movements) and mismatches or gaps (lateral or downward movements).
+
+When the sequences under comparison are highly similar or closely related, the path of optimal alignment is expected to predominantly traverse diagonally, reflecting a substantial degree of matching between the sequences.
+Such clear, uninterrupted diagonal lines illustrate sequences of consecutive matches, enabling direct interpretation of the alignment from the dot plot.
+This direct reading of alignments becomes particularly feasible when the sequences are closely related, as a continuous diagonal line (or lines) stretching from the upper left to the lower right corner of the dot plot allows for the alignment to be intuitively "read" off the plot.
+By observing the path's direction changes, one can effortlessly deduce the sequence of matches and mismatches, including the strategic positioning of gaps, thereby offering a visually intuitive method to understand sequence alignment through dot plots.

content/alignment/multiple/_index.md

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+---
+title: Multiple sequence alignment
+type: docs
+weight: 4
+---
+
+> [!CAUTION]
+>
+> This page is a work in progress and is subject to change at any moment.
+
+Multiple Sequence Alignments (MSAs) are a cornerstone technique in bioinformatics.
+They enable scientists to align three or more biological sequences—such as proteins, DNA, or RNA—to unearth regions of similarity.
+These similarities can indicate functional, structural, or evolutionary relationships between the sequences, offering insights into the molecular mechanisms of life.
+
+## Significance
+
+MSAs play a pivotal role in molecular biology and genetics by highlighting conserved sequences across species or protein families.
+These conserved elements are often crucial for biological function or structure, implying their importance throughout evolutionary history.
+By comparing sequences, researchers can infer phylogenetic relationships, understand evolutionary processes, and predict the function of new genes.
+Additionally, MSAs assist in identifying sequence motifs—short, conserved subsequences critical for protein function or specific biochemical activities.
+
+## Procedure
+
+The process begins with collecting sequences that potentially share a common ancestry or function.
+Using bioinformatics tools such as ClustalW, MUSCLE, or T-Coffee, these sequences are aligned to identify similar regions.
+The alignment is adjusted to maximize matching characters (amino acids or nucleotides) while minimizing gaps or mismatches.
+This can involve sophisticated computational algorithms, considering evolutionary events like mutations, insertions, and deletions.
+
+## Applications
+
+-   **Functional Annotation:** By aligning an unknown sequence with known sequences, researchers can predict the unknown's function based on shared motifs and conserved regions.
+-   **Structural Prediction:** MSAs can indicate critical structural elements preserved across species, aiding in the structural prediction of proteins.
+-   **Evolutionary Biology:** MSAs reveal the evolutionary relationships between sequences, helping to construct phylogenetic trees that trace lineage divergence and speciation events.
+-   **Drug Discovery:** Identifying conserved regions can help in designing drugs that target these sequences, crucial in combating diseases with a genetic basis.