Expected Preparations:
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Keywords: Sequence analysis by comparison; deterministic pattern matching; probabilistic pattern matching; HMMS; Neural Networks | |||||||||||
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Deliverables: Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit. Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don’t overlook these. Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page. |
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Evaluation: NA: This unit is not evaluated for course marks. |
Sequence analysis by pattern matching. NA NA
Task…
Let us perform a few simple sequence analyses using the online EMBOSS tools. EMBOSS (the European Molecular Biology laboratory Open Software Suite) combines a large number of simple but fundamental sequence analysis tools. The tools can be installed locally on your own machine, or run via a public Web interface. Google for EMBOSS explorer, public access points include http://emboss.bioinformatics.nl/ .
Access an EMBOSS Explorer service and explore some of the tools:
Task…
Local composition 1. Find pepinfo
under
the PROTEIN COMPOSITION heading. 1. Retrieve the MYSPE
Mbp1 related sequence from your R database, e.g. with
something like cat(db\(protein[db\)protein$name == “UMAG_1122”),
“sequence”]
1. Copy and paste the sequence into the input field.
1. Run with default parameters. 1. Scroll to the figures all the way at
the bottom. 1. Do the same in a separate window for yeast Mbp1. 1. Try
to compare … (kind of hard without reference, overlay and
expectation, isn’t it?)
Task…
Motifs 1. Find pepcoil
, an algorithm to
detect coiled coil(W)
motifs. 1. Run this with the MYSPE Mbp1 sequence and yeast Mbp1. 1. Try
to compare … do both sequences have coiled-coil motif predictions? Are
they annotated in approximately comparable regions of the respective
sequence?
Task…
Transmembrane sequences 1. Find tmap
.
Also find shuffleseq
. 1. Use your MYSPE sequence to
annotate transmembrane helices for your protein and for a few shuffled
sequences. The MYSPE is not expected to have TM helices, nor are the
shuffled sequences expected to have any. If you do find
some, these are most likely “false positives”.
>gi|6322500|ref|NP_012574.1| Gef1p [Saccharomyces cerevisiae S288c]
MPTTYVPINQPIGDGEDVIDTNRFTNIPETQNFDQFVTIDKIAEENRPLSVDSDREFLNSKYRHYREVIW
DRAKTFITLSSTAIVIGCIAGFLQVFTETLVNWKTGHCQRNWLLNKSFCCNGVVNEVTSTSNLLLKRQEF
ECEAQGLWIAWKGHVSPFIIFMLLSVLFALISTLLVKYVAPMATGSGISEIKVWVSGFEYNKEFLGFLTL
VIKSVALPLAISSGLSVGKEGPSVHYATCCGYLLTKWLLRDTLTYSSQYEYITAASGAGVAVAFGAPIGG
VLFGLEEIASANRFNSSTLWKSYYVALVAITTLKYIDPFRNGRVILFNVTYDRDWKVQEIPIFIALGIFG
GLYGKYISKWNINFIHFRKMYLSSWPVQEVLFLATLTALISYFNEFLKLDMTESMGILFHECVKNDNTST
FSHRLCQLDENTHAFEFLKIFTSLCFATVIRALLVVVSYGARVPAGIFVPSMAVGATFGRAVSLLVERFI
SGPSVITPGAYAFLGAAATLSGITNLTLTVVVIMFELTGAFMYIIPLMIVVAITRIILSTSGISGGIADQ
MIMVNGFPYLEDEQDEEEEETLEKYTAEQLMSSKLITINETIYLSELESLLYDSASEYSVHGFPITKDED
KFEKEKRCIGYVLKRHLASKIMMQSVNSTKAQTTLVYFNKSNEELGHRENCIGFKDIMNESPISVKKAVP
VTLLFRMFKELGCKTIIVEESGILKGLVTAKDILRFKRIKYREVHGAKFTYNEALDRRCWSVIHFIIKRF
TTNRNGNVI
Try to familiarize yourself with the offerings in the EMBOSS package.
I find some of the nucleic acid tools indispensable in the lab, such as
restriction-site mapping tools (remap), and I frequently use the
alignment tools Needle
and Water
, but by and
large the utility of many of the components–while fast, efficient and
straightforward to use– suffers from lack of reference and comparison
and from terse output. The routines show their conceptual origin in the
1970s and 1980s.
It’s interesting to consider how this collection of tools that were carefully designed some thirty years ago, as an open source replacement for a set of software tools - the GCG package - that was indispensable for molecular biology labs in the 80s and 90s, but whose cost had become prohibitive - has slowly lost relevance due to a change in computational paradigms. Everything these tools do is still correct. But fundamentally this is a building block approach, and the field has turned to programming solutions instead - as exemplified in seqinr and other R packages, and the Bioconductor project.
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