Results 81 to 90 of about 187,791 (308)

Towards Automatic Topical Classification of LOD Datasets. [PDF]

open access: yes, 2015
The datasets that are part of the Linking Open Data cloud diagramm (LOD cloud) are classified into the following topical categories: media, government, publications, life sciences, geographic, social networking, user-generated content, and cross-domain. The topical categories were manually assigned to the datasets.
Meusel, Robert   +3 more
openaire   +2 more sources

Reconstructing enzyme evolution by protein engineering

open access: yesFEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler   +2 more
wiley   +1 more source

Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis

open access: yesFrontiers in Artificial Intelligence, 2020
With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages.
Rania Albalawi   +2 more
doaj   +1 more source

Identification of the plant mitochondrial OrfX protein: A mass spectrometry approach

open access: yesFEBS Letters, EarlyView.
The mitochondrial genome of plants contains an open reading frame, orfx, which encodes a rare protein that has so far escaped mass spectrometric detection. The protein resembles the c‐subunit of bacterial twin‐arginine‐motif‐dependent protein translocases (TatC).
Matthias Döring   +3 more
wiley   +1 more source

Statistically validated network for analysing textual data

open access: yesApplied Network Science
This paper presents a novel methodology, called Word Co-occurrence SVN topic model (WCSVNtm), for document clustering and topic modeling in textual datasets.
Andrea Simonetti   +3 more
doaj   +1 more source

Enhanced Fault Diagnosis Method for Tractors Using Random Forest Algorithm [PDF]

open access: yesAdvances in Engineering and Intelligence Systems
In this study, we initially introduce a robust method to categorize large groups of educators into distinct communities, termed "genres," based on their shared instructional preferences.
Milad Mohebbi, Yalda Mohebbi
doaj   +1 more source

EDNRB‐dependent endothelin signaling reduces proliferation and promotes proneural‐to‐mesenchymal transition in gliomas

open access: yesMolecular Oncology, EarlyView.
Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau   +36 more
wiley   +1 more source

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang   +12 more
wiley   +1 more source

sifds: Swedish inflation forecast data set 1999:Q2–2005:Q2 [PDF]

open access: yes
A data set consisting of 25 forecasts (1999–2005) by Sveriges Riksbank (RB) and 18 forecasts (2001–2005) by Konjunkturinstitutet (KI) for Swedish inflation rates measured as CPI and KPIX.Inflation forecast data; inflation data; Sweden; CPI; KPIX ...
Lundholm, Michael
core  

TR-GPT-CF: A Topic Refinement Method Using GPT and Coherence Filtering

open access: yesApplied Sciences
Traditional topic models are effective at uncovering patterns within large text corpora but often struggle with capturing the contextual nuances necessary for meaningful interpretation.
Ika Widiastuti, Hwan-Seung Yong
doaj   +1 more source

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