Results 91 to 100 of about 93,376 (303)
FEBS Open Bio, EarlyView.Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
Time-series forecasting through recurrent topology
Communications EngineeringTime-series forecasting is a practical goal in many areas of science and engineering. Common approaches for forecasting future events often rely on highly parameterized or black-box models.
Taylor Chomiak, Bin Hu
doaj +1 more source
Survey of Transformer-based Time Series Forecasting Methods [PDF]
Jisuanji kexueTime series forecasting,a critical technique for analyzing historical data to predict future trends,has been widely applied in fields such as finance and meteorology.However,traditional methods like the autoregressive moving average model and exponential
CHEN Jiajun, LIU Bo, LIN Weiwei, ZHENG Jianwen, XIE Jiachen
doaj +1 more source
Nonparametric time series forecasting with dynamic updating [PDF]
We present a nonparametric method to forecast a seasonal univariate time series, and propose four dynamic updating methods to improve point forecast accuracy. Our methods consider a seasonal univariate time series as a functional time series.
Han Lin Shang, Rob J Hyndman
core
FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Ondaietas e previsão de séries de tempo: uma análise empírica
Economia Aplicada, 2003 This paper presents three case studies in time series forecasting. We try to compare the use of traditional ARIMA models with an alternative method that combines of ARIMA and Wavelets models. Two different approaches are applied.
Guilherme V. Homsy +2 more
doaj
Screening and epitope characterization of Nidogen‐2‐specific nanobodies
FEBS Open Bio, EarlyView.Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen +9 more
wiley +1 more source
Neural network analysis in time series forecasting
Российский технологический журналObjectives. To build neural network models of time series (LSTM, GRU, RNN) and compare the results of forecasting with their mutual help and the results of standard models (ARIMA, ETS), in order to ascertain in which cases a certain group of models ...
B. Pashshoev, D. A. Petrusevich
doaj +1 more source
Short-term electricity price forecasting with time series models: A review and evaluation [PDF]
We investigate the forecasting power of different time series models for electricity spot prices. The models include different specifications of linear autoregressive time series with heteroscedastic noise and/or additional fundamental variables and non ...
Rafal Weron, Adam Misiorek
core
FEBS Open Bio, EarlyView.Chemotherapy side effects significantly impact cancer survivors' quality of life. Using protein levels in blood samples from breast cancer patients before and after 12 weeks of taxane treatment, we detected treatment‐dependent changes in calcium signaling and aging pathways associated with cancer recurrence.
Saira Munshani +6 more
wiley +1 more source