Choosing the right algorithm with hints from complexity theory

Wang, Shouda; Zheng, Weijie; Doerr, Benjamin

doi:10.1016/j.ic.2023.105125

Cited by 5 publications

(1 citation statement)

References 58 publications

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“…The model proposed here considers the interaction between the sphingolipid membrane rafts and the concentration of the amyloid complex and analyses, according to a dynamic represented in figure 1, the increase in the "oligomer-membrane" complex until the threshold concentration that rapidly leads to the process of membrane catalysis and the consequent "extraction" of phospholipids. Based on literature surveys, a step by step framework, incorporated with machine learning inference algorithm [23], [24] was utilized to infer the probabilities as illustrated in figure ??. It is also interesting to note the cooperative process that occurs at the level of the recruitment of sphingolipid rafts where there is an amplification of the phenomenon due to a sort of facilitation in this recruitment since as the concentration of the "oligomer-membrane" complex increases, the concentration of recruited sphingolipid rafts.…”

Section: Resultsmentioning

confidence: 99%

Interaction between the sphingolipid membrane rafts and the concentration of the amyloid complex and analyses

Nutini,

Sohail

2024

Preprint

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Amyloidosis diseases are a heterogeneous group of pathologies that have a strong impact on current society both in global health and in the economic system of each country. The analysis of how the entry of the toxic species identified into the amyloid oligomeric elements occurs is the main objective of much research in the sector. In this work, we analyze a hypothesis of the entry of oligomers into the membrane whereby, after a massive recruitment of the sphingolipid rafts thanks to their connection with the oligomers, a cleansing of the membrane itself occurs. This pathological event creates a sort of pore which, subsequently stabilized, allows the oligomers to enter the cell. In this work, we build an entry model based on dynamic networks that investigates the fundamental mechanisms that lead to the entry of amyloid oligomers into the cell after having formed a critical concentration in the oligomer-membrane complex which, thanks to the conformational changes affecting the oligomers themselves, carries out the cleansing of the membrane and the entry of these pathogenic elements. The global dynamic network is divided into subnetworks which are expressed by algorithms that identify both time and threshold concentration as the fundamental moment in triggering the entire pathological process.

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Section: Resultsmentioning

confidence: 99%

Interaction between the sphingolipid membrane rafts and the concentration of the amyloid complex and analyses

Nutini,

Sohail

2024

Preprint

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DNA-SaM, a robust system for large-scale data storage

Huang,

Wang,

et al. 2024

Preprint

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DNA data storage offers a viable strategy to address the impending data explosion. Early attempts to harness DNA as a storage medium have encountered scalability limitations, largely due to the complexity of codec algorithms, the generation of biochemically harmful sequences and lack of a robust architecture. We present "DNA-SaM", a novel system designed for DNA data storage, which achieves linear computational complexity and strict bio-constraint adherence, ensuring high coding efficiency and fidelity. It encoded data at speeds surpassing classic systems by over 2 orders of magnitude, with this superiority changes across various encoding algorithms. Importantly, DNA-SaM effectively eliminates any sequence that could be deleterious to in vitro and in vivo biochemical processes, including homopolymer runs, tandem repeat motifs, and potential promoter sequences, etc. It also involves an advanced DNA data storage architecture that incorporates a two-tiered indexing system and a novel "storage unit" distribution paradigm for large-scale data storage. It is further validated by practical data storage both in vitro and in vivo with a 100% success rate. Our system is capable of storing data over 1039 PB, which marks a critical advancement in the scalability of DNA-based data storage.

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