Results 51 to 60 of about 93,376 (303)

Neural Networks for Financial Time Series Forecasting

Entropy, 2022
Financial and economic time series forecasting has never been an easy task due to its sensibility to political, economic and social factors. For this reason, people who invest in financial markets and currency exchange are usually looking for robust ...
Kady Sako, Berthine Nyunga Mpinda, Paulo Canas Rodrigues   +2 more
doaj   +1 more source

Tourism Time Series Forecast

, 2015
In this chapter four combinations of input features and the feedforward, cascade forward and recurrent architectures are compared for the task of forecast tourism time series. The input features of the ANNs consist in the combination of the previous 12 months, the index time modeled by two nodes used to the year and month and one input with the daily ...
Teixeira, João Paulo, Fernandes, Paula Odete   +1 more
openaire   +2 more sources

Cell geometry and membrane protein crowding constrain Escherichia coli growth rate, overflow metabolism, respiration, and maintenance energy

FEBS Letters, EarlyView.
The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson, Tomáš Gedeon, Mauricio Garcia Benitez, Campbell Putnam, William R. Harcombe, Radhakrishnan Mahadevan, Ashley E. Beck   +6 more
wiley   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS 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, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Forecasting Hierarchical Time Series in Power Generation

Energies, 2020
Academic attention is being paid to the study of hierarchical time series. Especially in the electrical sector, there are several applications in which information can be organized into a hierarchical structure.
Tiago Silveira Gontijo, Marcelo Azevedo Costa   +1 more
doaj   +1 more source

Forecasting time series with constraints

CoRR
Time series forecasting presents unique challenges that limit the effectiveness of traditional machine learning algorithms. To address these limitations, various approaches have incorporated linear constraints into learning algorithms, such as generalized additive models and hierarchical forecasting.
Nathan Doumèche, Francis R. Bach, Éloi Bedek, Gérard Biau, Claire Boyer, Yannig Goude   +5 more
openaire   +2 more sources

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Pre‐analytical optimization of cell‐free DNA and extracellular vesicle‐derived DNA for mutation detection in liquid biopsies

Molecular Oncology, EarlyView.
Pre‐analytical handling critically determines liquid biopsy performance. This study defines practical best‐practice conditions for cell‐free DNA (cfDNA) and extracellular vesicle–derived DNA (evDNA), showing how processing time, storage conditions, tube type, and plasma input volume affect DNA integrity and mutation detection.
Jonas Dohmen, Lucrezia De Santis, Bret M. Stephens, Vincent Bernard, Jörg C. Kalff, Lara Braun, Phillipp Leyendecker, Johannes Röttgen, Daniel Weissinger, Anirban Maitra, Paola A. Guerrero, Alexander Semaan   +11 more
wiley   +1 more source

Machine-Learning Models for Sales Time Series Forecasting

Data, 2019
In this paper, we study the usage of machine-learning models for sales predictive analytics. The main goal of this paper is to consider main approaches and case studies of using machine learning for sales forecasting.
Bohdan M. Pavlyshenko
doaj   +1 more source

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

Molecular 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, Ayesha Alvero, Yi Qin, Mingjin Wang, Alexandra Fox, Yanfeng Li, Michael Millman, Amy Kemper, Gil Mor, Xian Shuang Liu, Michael Chopp, Zheng Gang Zhang, Yi Zhang   +12 more
wiley   +1 more source