Results 61 to 70 of about 108,016 (310)

Semi-supervised learning paradigm analysis for classification of multimodal data

Науковий вісник Ужгородського університету. Серія: Математика і інформатика, 2021
The paper considers machine learning algorithms. The focus is on semi-controlled learning, which seems to be the balance between teaching accuracy with a teacher and the cost of teaching methods without a teacher.
Н. Бойко
doaj   +1 more source

Application of support vector machines on the basis of the first Hungarian bankruptcy model [PDF]

, 2013
In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of ...
Virág, Miklós, Nyitrai, Tamás
core   +1 more source

Large‐scale bidirectional arrayed genetic screens identify OXR1 and EMC4 as modifiers of αSynuclein aggregation

FEBS Open Bio, EarlyView.
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane, Lea Nikolić, Lorenzo Maraio, Thomas Goiran, Nathan Karpilovsky, Stefano Sellitto, Vangelis Bouris, Jiang‐An Yin, Ronald Melki, Edward A Fon, Adriano Aguzzi, Elena De Cecco   +11 more
wiley   +1 more source

Convex Optimization of Support Vector Machines

四川大学学报. 自然科学版, 2016
Support Vector Machine (SVM) is a machine learning method based on statistical learning theory. Because of its superior learning performance. It has become the hot topic of pattern recognition, data mining, machine learning and other large data ...
ZHOU Zheng-Song, LI Yao, TAO De-Yuan
doaj  

Support vector machines for TEC seismo-ionospheric anomalies detection [PDF]

Annales Geophysicae, 2013
Using time series prediction methods, it is possible to pursue the behaviors of earthquake precursors in the future and to announce early warnings when the differences between the predicted value and the observed value exceed the predefined threshold ...
M. Akhoondzadeh
doaj   +1 more source

Convolutional Support Vector Machine

CoRR, 2020
The support vector machine (SVM) and deep learning (e.g., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. Nonetheless, smaller datasets may be very important, costly, and not easy to obtain in a short time.
openaire   +2 more sources

Mass spectrometry based identification of AMP‐O‐Tris generated by Thermococcus onnurineus Cas10

FEBS Open Bio, EarlyView.
Isolated Thermococcus onnurineus Cas10 generates the noncanonical ATP‐derived product AMP‐O‐Tris while in Tris‐containing buffer as identified via mass spectrometry, revealing relaxed nucleophile selectivity under isolated conditions. These findings suggest that multiprotein Csm complex assembly restricts Cas10 reactivity toward canonical cyclic ...
Su‐Jin Lee, Ga Seul Lee, JinHan Kim, Kwang‐Hyun Park, Seong‐Ryung Go, Jeong Hee Moon, Eui‐Jeon Woo   +6 more
wiley   +1 more source

Transmembrane protein topology prediction using support vector machines

BMC Bioinformatics, 2009
Background Alpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are
Nugent Timothy, Jones David T
doaj   +1 more source

Versatile vector tools for efficient protein screening across multiple expression systems

FEBS Open Bio, EarlyView.
A unified vector toolkit enables rapid protein expression screening across E. coli, insect, and mammalian cells. A single primer pair amplifies the target gene, which is inserted into any vector via a standardized interface. This streamlined workflow eliminates repeated cloning steps, accelerating the identification of optimal expression conditions for
Zhimin Zhu, Yaqing Liu, Lei Qin, Feng Yu, Qisheng Wang, Yahui Liu   +5 more
wiley   +1 more source

Unsupervised two-class & multi-class support vector machines for abnormal traffic characterization. [PDF]

, 2009
Although measurement-based real-time traffic classification has received considerable research attention, the timing constraints imposed by the high accuracy requirements and the learning phase of the algorithms employed still remain a challenge. In this
Kim, Hyun-chul, Hutchison, D., Pezaros, D., Pezaros, Dimitrios P., Marnerides, A., Kim, H., Marnerides, Angelos, Hutchison, David   +7 more
core