153 research outputs found
Ten Quick Tips for Using a Raspberry Pi
Much of biology (and, indeed, all of science) is becoming increasingly
computational. We tend to think of this in regards to algorithmic approaches
and software tools, as well as increased computing power. There has also been a
shift towards slicker, packaged solutions--which mirrors everyday life, from
smart phones to smart homes. As a result, it's all too easy to be detached from
the fundamental elements that power these changes, and to see solutions as
"black boxes". The major goal of this piece is to use the example of the
Raspberry Pi--a small, general-purpose computer--as the central component in a
highly developed ecosystem that brings together elements like external
hardware, sensors and controllers, state-of-the-art programming practices, and
basic electronics and physics, all in an approachable and useful way. External
devices and inputs are easily connected to the Pi, and it can, in turn, control
attached devices very simply. So whether you want to use it to manage
laboratory equipment, sample the environment, teach bioinformatics, control
your home security or make a model lunar lander, it's all built from the same
basic principles. To quote Richard Feynman, "What I cannot create, I do not
understand".Comment: 12 pages, 2 figure
An Introduction to Programming for Bioscientists: A Python-based Primer
Computing has revolutionized the biological sciences over the past several
decades, such that virtually all contemporary research in the biosciences
utilizes computer programs. The computational advances have come on many
fronts, spurred by fundamental developments in hardware, software, and
algorithms. These advances have influenced, and even engendered, a phenomenal
array of bioscience fields, including molecular evolution and bioinformatics;
genome-, proteome-, transcriptome- and metabolome-wide experimental studies;
structural genomics; and atomistic simulations of cellular-scale molecular
assemblies as large as ribosomes and intact viruses. In short, much of
post-genomic biology is increasingly becoming a form of computational biology.
The ability to design and write computer programs is among the most
indispensable skills that a modern researcher can cultivate. Python has become
a popular programming language in the biosciences, largely because (i) its
straightforward semantics and clean syntax make it a readily accessible first
language; (ii) it is expressive and well-suited to object-oriented programming,
as well as other modern paradigms; and (iii) the many available libraries and
third-party toolkits extend the functionality of the core language into
virtually every biological domain (sequence and structure analyses,
phylogenomics, workflow management systems, etc.). This primer offers a basic
introduction to coding, via Python, and it includes concrete examples and
exercises to illustrate the language's usage and capabilities; the main text
culminates with a final project in structural bioinformatics. A suite of
Supplemental Chapters is also provided. Starting with basic concepts, such as
that of a 'variable', the Chapters methodically advance the reader to the point
of writing a graphical user interface to compute the Hamming distance between
two DNA sequences.Comment: 65 pages total, including 45 pages text, 3 figures, 4 tables,
numerous exercises, and 19 pages of Supporting Information; currently in
press at PLOS Computational Biolog
Claws, Disorder, and Conformational Dynamics of the C Terminal Region of Human Desmoplakin
Multicellular
organisms consist of cells that interact via elaborate
adhesion complexes. Desmosomes are membrane-associated adhesion complexes
that mechanically tether the cytoskeletal intermediate filaments (IFs)
between two adjacent cells, creating a network of tough connections
in tissues such as skin and heart. Desmoplakin (DP) is the key desmosomal
protein that binds IFs, and the DP·IF association poses a quandary:
desmoplakin must stably and tightly bind IFs to maintain the structural
integrity of the desmosome. Yet, newly synthesized DP must traffic
along the cytoskeleton to the site of nascent desmosome assembly without
“sticking” to the IF network, implying weak or transient
DP···IF contacts. Recent work reveals that these contacts
are modulated by post-translational modifications (PTMs) in DP’s
C-terminal tail (DP<sub>CTT</sub>). Using molecular dynamics simulations,
we have elucidated the structural basis of these PTM-induced effects.
Our simulations, nearing 2 ÎĽs in aggregate, indicate that phosphorylation
of S2849 induces an “arginine claw” in desmoplakin’s
C-terminal tail. If a key arginine, R2834, is methylated, the DP<sub>CTT</sub> preferentially samples conformations that are geometrically
well-suited as substrates for processive phosphorylation by the cognate
kinase GSK3. We suggest that DP<sub>CTT</sub> is a molecular switch
that modulates, via its conformational dynamics, DP’s overall
efficacy as a substrate for GSK3. Finally, we show that the fluctuating
DP<sub>CTT</sub> can contact other parts of DP, suggesting a competitive
binding mechanism for the modulation of DP···IF interactions
A Birds-Eye (Re)View of Acid-Suppression Drugs, COVID-19, and the Highly Variable Literature
This Perspective examines a recent surge of information regarding the potential benefits of acid-suppression drugs in the context of COVID-19, with a particular eye on the great variability (and, thus, confusion) that has arisen across the reported findings, at least as regards the popular antacid famotidine. The degree of inconsistency and discordance reflects contradictory conclusions from independent, clinical-based studies that took roughly similar approaches, in terms of both experimental design (retrospective, observational, cohort-based, etc.) and statistical analysis workflows (propensity-score matching and stratification into sub-cohorts, etc.). The contradictions and potential confusion have ramifications for clinicians faced with choosing therapeutically optimal courses of intervention: e.g., do any potential benefits of famotidine suggest its use in a particular COVID-19 case? (If so, what administration route, dosage regimen, duration, etc. are likely optimal?) As succinctly put this March in Freedberg et al. (2021), "…several retrospective studies show relationships between famotidine and outcomes in COVID-19 and several do not." Beyond the pressing issue of possible therapeutic indications, the conflicting data and conclusions related to famotidine must be resolved before its inclusion/integration in ontological and knowledge graph (KG)-based frameworks, which in turn are useful for drug discovery and repurposing. As a broader methodological issue, note that reconciling inconsistencies would bolster the validity of meta-analyses which draw upon the relevant data-sources. And, perhaps most broadly, developing a system for treating inconsistencies would stand to improve the qualities of both 1) real world evidence-based studies (retrospective), on the one hand, and 2) placebo-controlled, randomized multi-center clinical trials (prospective), on the other hand. In other words, a systematic approach to reconciling the two types of studies would inherently improve the quality and utility of each type of study individually
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