ﻻ يوجد ملخص باللغة العربية
We axiomatize the molecular-biology reasoning style, show compliance of the standard reference: Ptashne, A Genetic Switch, and present proof-theory-induced technologies to help infer phenotypes and to predict life cycles from genotypes. The key is to note that `reductionist discipline entails constructive reasoning: any proof of a compound property can be decomposed to proofs of constituent properties. Proof theory makes explicit the inner structure of the axiomatized reasoning style and allows the permissible dynamics to be presented as a mode of computation that can be executed and analyzed. Constructivity and execution guarantee simulation when working over domain-specific languages. Here, we exhibit phenotype properties for genotype reasons: a molecular-biology argument is an open-system concurrent computation that results in compartment changes and is performed among processes of physiology change as determined from the molecular programming of given DNA. Life cycles are the possible sequentializations of the processes. A main implication of our construction is that formal correctness provides a complementary perspective on science that is as fundamental there as for pure mathematics. The bulk of the presented work has been verified formally correct by computer.
Scientific objectivity was not a problem in the early days of molecular biology. However, relativism seems to have invaded some areas of the field, damaging the objectivity of its analyses. This review reports on the status of this issue by investigating a number of cases.
The Virtual Institute for Integrative Biology (VIIB) is a Latin American initiative for achieving global collaborative e-Science in the areas of bioinformatics, genome biology, systems biology, metagenomics, medical applications and nanobiotechnolgy.
Biological molecules chose one of two structurally, chiral systems which are related by reflection in a mirror. It is proposed that this choice was made, causally, by magnetically polarized and physically chiral cosmic-rays, which are known to have a
Chalmers famously identified pinpointing an explanation for our subjective experience as the hard problem of consciousness. He argued that subjective experience constitutes a hard problem in the sense that its explanation will ultimately require new
Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. A