79 research outputs found
Inconsistent boundaries
Research on this paper was supported by a grant from the Marsden Fund, Royal Society of New Zealand.Mereotopology is a theory of connected parts. The existence of boundaries, as parts of everyday objects, is basic to any such theory; but in classical mereotopology, there is a problem: if boundaries exist, then either distinct entities cannot be in contact, or else space is not topologically connected (Varzi in Noûs 31:26–58, 1997). In this paper we urge that this problem can be met with a paraconsistent mereotopology, and sketch the details of one such approach. The resulting theory focuses attention on the role of empty parts, in delivering a balanced and bounded metaphysics of naive space.PostprintPeer reviewe
Technology dictates algorithms: Recent developments in read alignment
Massively parallel sequencing techniques have revolutionized biological and
medical sciences by providing unprecedented insight into the genomes of humans,
animals, and microbes. Modern sequencing platforms generate enormous amounts of
genomic data in the form of nucleotide sequences or reads. Aligning reads onto
reference genomes enables the identification of individual-specific genetic
variants and is an essential step of the majority of genomic analysis
pipelines. Aligned reads are essential for answering important biological
questions, such as detecting mutations driving various human diseases and
complex traits as well as identifying species present in metagenomic samples.
The read alignment problem is extremely challenging due to the large size of
analyzed datasets and numerous technological limitations of sequencing
platforms, and researchers have developed novel bioinformatics algorithms to
tackle these difficulties. Importantly, computational algorithms have evolved
and diversified in accordance with technological advances, leading to todays
diverse array of bioinformatics tools. Our review provides a survey of
algorithmic foundations and methodologies across 107 alignment methods
published between 1988 and 2020, for both short and long reads. We provide
rigorous experimental evaluation of 11 read aligners to demonstrate the effect
of these underlying algorithms on speed and efficiency of read aligners. We
separately discuss how longer read lengths produce unique advantages and
limitations to read alignment techniques. We also discuss how general alignment
algorithms have been tailored to the specific needs of various domains in
biology, including whole transcriptome, adaptive immune repertoire, and human
microbiome studies
SEK: sparsity exploiting k-mer-based estimation of bacterial community composition.
MOTIVATION: Estimation of bacterial community composition from a high-throughput sequenced sample is an important task in metagenomics applications. As the sample sequence data typically harbors reads of variable lengths and different levels of biological and technical noise, accurate statistical analysis of such data is challenging. Currently popular estimation methods are typically time-consuming in a desktop computing environment.
RESULTS: Using sparsity enforcing methods from the general sparse signal processing field (such as compressed sensing), we derive a solution to the community composition estimation problem by a simultaneous assignment of all sample reads to a pre-processed reference database. A general statistical model based on kernel density estimation techniques is introduced for the assignment task, and the model solution is obtained using convex optimization tools. Further, we design a greedy algorithm solution for a fast solution. Our approach offers a reasonably fast community composition estimation method, which is shown to be more robust to input data variation than a recently introduced related method.
AVAILABILITY AND IMPLEMENTATION: A platform-independent Matlab implementation of the method is freely available at http://www.ee.kth.se/ctsoftware; source code that does not require access to Matlab is currently being tested and will be made available later through the above Web site
Critical Assessment of Metagenome Interpretation:A benchmark of metagenomics software
International audienceIn metagenome analysis, computational methods for assembly, taxonomic profilingand binning are key components facilitating downstream biological datainterpretation. However, a lack of consensus about benchmarking datasets andevaluation metrics complicates proper performance assessment. The CriticalAssessment of Metagenome Interpretation (CAMI) challenge has engaged the globaldeveloper community to benchmark their programs on datasets of unprecedentedcomplexity and realism. Benchmark metagenomes were generated from newlysequenced ~700 microorganisms and ~600 novel viruses and plasmids, includinggenomes with varying degrees of relatedness to each other and to publicly availableones and representing common experimental setups. Across all datasets, assemblyand genome binning programs performed well for species represented by individualgenomes, while performance was substantially affected by the presence of relatedstrains. Taxonomic profiling and binning programs were proficient at high taxonomicranks, with a notable performance decrease below the family level. Parametersettings substantially impacted performances, underscoring the importance ofprogram reproducibility. While highlighting current challenges in computationalmetagenomics, the CAMI results provide a roadmap for software selection to answerspecific research questions
On the Mathematical Constitution and Explanation of Physical Facts
The mathematical nature of modern physics suggests that mathematics is bound to play some role in explaining physical reality. Yet, there is an ongoing controversy about the prospects of mathematical explanations of physical facts and their nature. A common view has it that mathematics provides a rich and indispensable language for representing physical reality but that, ontologically, physical facts are not mathematical and, accordingly, mathematical facts cannot really explain physical facts. In what follows, I challenge this common view. I argue that, in addition to its representational role, in modern physics mathematics is constitutive of the physical. Granted the mathematical constitution of the physical, I propose an account of explanation in which mathematical frameworks, structures, and facts explain physical facts. In this account, mathematical explanations of physical facts are either species of physical explanations of physical facts in which the mathematical constitution of some physical facts in the explanans are highlighted, or simply explanations in which the mathematical constitution of physical facts are highlighted. In highlighting the mathematical constitution of physical facts, mathematical explanations of physical facts deepen and increase the scope of the understanding of the explained physical facts. I argue that, unlike other accounts of mathematical explanations of physical facts, the proposed account is not subject to the objection that mathematics only represents the physical facts that actually do the explanation. I conclude by briefly considering the implications that the mathematical constitution of the physical has for the question of the unreasonable effectiveness of the use of mathematics in physics
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