Utilization of Time Series Tools in Life-sciences and Neuroscience

Abstract

Time series tools are part and parcel of modern day research. Their usage in the biomedical field; specifically, in neuroscience, has not been previously quantified. A quantification of trends can tell about lacunae in the current uses and point towards future uses. We evaluated the principles and applications of few classical time series tools, such as Principal Component Analysis, Neural Networks, common Auto-regression Models, Markov Models, Hidden Markov Models, Fourier Analysis, Spectral Analysis, in addition to diverse work, generically lumped under time series category. We quantified the usage from two perspectives, one, information technology professionals’, other, researchers utilizing these tools for biomedical and neuroscience research. For understanding trends from the information technology perspective, we evaluated two of the largest open source question and answer databases of Stack Overflow and Cross Validated. We quantified the trends in their application in the biomedical domain, and specifically neuroscience, by searching literature and application usage on PubMed. While the use of all the time series tools continues to gain popularity in general biomedical and life science research, and also neuroscience, and so have been the total number of questions asked on Stack overflow and Cross Validated, the total views to questions on these are on a decrease in recent years, indicating well established texts, algorithms, and libraries, resulting in engineers not looking for what used to be common questions a few years back. The use of these tools in neuroscience clearly leaves room for improvement.

Inteligência computacional no mercado financeiro: uma revisão de técnicas para automação de operações

“…Com o avanço da tecnologia, temos visto um progresso significativo no desenvolvimento de métodos baseados em computador para diversas áreas, incluindo a financeira (Vogl et al, 2022). O desenvolvimento de modelos precisos é difícil, pois a previsão do mercado financeiro depende não apenas de um único fator, mas de vários, que incluem, política, oferta e demanda, calamidades naturais, notícias, dados de mídia social, produção da empresa, títulos estatais, preço histórico, bem como a economia do país (Gujral, et al, 2020). Dessa forma, um modelo de previsão que considera apenas uma característica pode não produzir resultados precisos.…”

Measurement of Autophagy Activity Reveals Time-Dependent, Bacteria-Specific Turnover during Mycobacterium tuberculosis Infection

“…The significance of time as a major determinant of the outcome of biological experiments cannot be overemphasized [ 8 , 9 , 10 , 11 ]. Most biological processes are highly dynamic and are temporally regulated.…”