Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

Universality of the break-up profile for the KdV equation in the small dispersion limit using the Riemann-Hilbert approach

We obtain an asymptotic expansion for the solution of the Cauchy problem for the Korteweg-de Vries (KdV) equation in the small dispersion limit near the point of gradient catastrophe (x_c,t_c) for the solution of the dispersionless equation. The sub-leading term in this expansion is described by the smooth solution of a fourth order ODE, which is a higher order analogue to the Painleve I equation. This is in accordance with a conjecture of Dubrovin, suggesting that this is a universal phenomenon for any Hamiltonian perturbation of a hyperbolic equation. Using the Deift/Zhou steepest descent method applied on the Riemann-Hilbert problem for the KdV equation, we are able to prove the asymptotic expansion rigorously in a double scaling limit.Comment: 30 page

Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at s=13TeV

A search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state is presented. The analysis is based on proton-proton collision data recorded by the CMS detector in 2016–2018 at a centre-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 138 fb−1. The search is sensitive to resonances with masses between 1.3 and 6TeV, decaying to bosons that are highly Lorentz-boosted such that each of the bosons forms a single large-radius jet. Machine learning techniques are employed to identify such jets. No significant excess over the estimated standard model background is observed. A maximum local significance of 3.6 standard deviations, corresponding to a global significance of 2.3 standard deviations, is observed at masses of 2.1 and 2.9 TeV. In a heavy vector triplet model, spin-1 Z′ and W′ resonances with masses below 4.8TeV are excluded at the 95% confidence level (CL). These limits are the most stringent to date. In a bulk graviton model, spin-2 gravitons and spin-0 radions with masses below 1.4 and 2.7TeV, respectively, are excluded at 95% CL. Production of heavy resonances through vector boson fusion is constrained with upper cross section limits at 95% CL as low as 0.1 fb. © 2023 The Author(s

Search for a heavy composite Majorana neutrino in events with dilepton signatures from proton-proton collisions at √s=13 Tev

Results are presented of a search for a heavy Majorana neutrino N ⠃ decaying into two same-flavor leptons ⠃ (electrons or muons) and a quark-pair jet. A model is considered in which the N ⠃ is an excited neutrino in a compositeness scenario. The analysis is performed using a sample of proton-proton collisions at & RADIC;s = 13 TeV recorded by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of 138 fb-1. The data are found to be in agreement with the standard model prediction. For the process in which the N ⠃ is produced in association with a lepton, followed by the decay of the N ⠃ to a same-flavor lepton and a quark pair, an upper limit at 95% confidence level on the product of the cross section and branching fraction is obtained as a function of the N ⠃ mass mN ⠃ and the compositeness scale ⠄. For this model the data exclude the existence of Ne (N & mu;) for mN ⠃ below 6.0 (6.1) TeV, at the limit where mN ⠃ is equal to ⠄. For mN ⠃ N 1 TeV, values of ⠄ less than 20 (23) TeV are excluded. These results represent a considerable improvement in sensitivity, covering a larger parameter space than previous searches in pp collisions at 13 TeV.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/). Funded by SCOAP3

Towards deployment-centric multimodal AI beyond vision and language

Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction and decision-making across disciplines such as healthcare, science and engineering. However, most multimodal AI advances focus on models for vision and language data, and their deployability remains a key challenge. We advocate a deployment-centric workflow that incorporates deployment constraints early on to reduce the likelihood of undeployable solutions, complementing data-centric and model-centric approaches. We also emphasize deeper integration across multiple levels of multimodality through stakeholder engagement and interdisciplinary collaboration to broaden the research scope beyond vision and language. To facilitate this approach, we identify common multimodal-AI-specific challenges shared across disciplines and examine three real-world use cases: pandemic response, self-driving car design and climate change adaptation, drawing expertise from healthcare, social science, engineering, science, sustainability and finance. By fostering interdisciplinary dialogue and open research practices, our community can accelerate deployment-centric development for broad societal impact

Vascular Remodeling in Health and Disease

The term vascular remodeling is commonly used to define the structural changes in blood vessel geometry that occur in response to long-term physiologic alterations in blood flow or in response to vessel wall injury brought about by trauma or underlying cardiovascular diseases.1, 2, 3, 4 The process of remodeling, which begins as an adaptive response to long-term hemodynamic alterations such as elevated shear stress or increased intravascular pressure, may eventually become maladaptive, leading to impaired vascular function. The vascular endothelium, owing to its location lining the lumen of blood vessels, plays a pivotal role in regulation of all aspects of vascular function and homeostasis.5 Thus, not surprisingly, endothelial dysfunction has been recognized as the harbinger of all major cardiovascular diseases such as hypertension, atherosclerosis, and diabetes.6, 7, 8 The endothelium elaborates a variety of substances that influence vascular tone and protect the vessel wall against inflammatory cell adhesion, thrombus formation, and vascular cell proliferation.8, 9, 10 Among the primary biologic mediators emanating from the endothelium is nitric oxide (NO) and the arachidonic acid metabolite prostacyclin [prostaglandin I2 (PGI2)], which exert powerful vasodilatory, antiadhesive, and antiproliferative effects in the vessel wall

Phylogenomics and the rise of the angiosperms

Angiosperms are the cornerstone of most terrestrial ecosystems and human livelihoods1,2. A robust understanding of angiosperm evolution is required to explain their rise to ecological dominance. So far, the angiosperm tree of life has been determined primarily by means of analyses of the plastid genome3,4. Many studies have drawn on this foundational work, such as classification and first insights into angiosperm diversification since their Mesozoic origins5,6,7. However, the limited and biased sampling of both taxa and genomes undermines confidence in the tree and its implications. Here, we build the tree of life for almost 8,000 (about 60%) angiosperm genera using a standardized set of 353 nuclear genes8. This 15-fold increase in genus-level sampling relative to comparable nuclear studies9 provides a critical test of earlier results and brings notable change to key groups, especially in rosids, while substantiating many previously predicted relationships. Scaling this tree to time using 200 fossils, we discovered that early angiosperm evolution was characterized by high gene tree conflict and explosive diversification, giving rise to more than 80% of extant angiosperm orders. Steady diversification ensued through the remaining Mesozoic Era until rates resurged in the Cenozoic Era, concurrent with decreasing global temperatures and tightly linked with gene tree conflict. Taken together, our extensive sampling combined with advanced phylogenomic methods shows the deep history and full complexity in the evolution of a megadiverse clade

Drama, Landscape and Memory: To Be is to Be in Place

This paper is based on research that sought to identify the cognitive and emotive effect of a collaborative drama event that took place in a unique landscape. Particular leitmotifs emerged from the research concerning identity and groups, the resonance of landscape, collective and childhood memory and the particularity of site-specific theatre. In this paper the author deconstructs two of these: landscape and memory. The concluding theories suggest that events of this nature can offer a sense of 'being in place'. The paper draws on 2 years of qualitative research of a many-layered theatre education project taking place, annually, in Cornwall, England. Approximately 70 undergraduate students have taken this project to 3,500 primary school pupils, 100 primary school staff and 2,000 adult audience members each year; the practical research is drawn from all these participants, particularly the students