The study and comparison of sequences of characters from a finite alphabet is relevant to various areas of science, notably molecular biology. The measurement of sequence similarity involves the consideration of the different possible sequence alignments in order to find an optimal one for which the “distance” between sequences is minimum. By associating a path in a lattice to each alignment, a geometric insight can be brought into the problem of finding an optimal alignment. This problem can then be solved by applying a dynamic programming algorithm. However, the computational effort grows rapidly with the number N of sequences to be compared $(O(l^N ))$, where l is the mean length of the sequences to be compared). It is proved here that knowledge of the measure of an arbitrarily chosen alignment can be used in combination with information from the pairwise alignments to considerably restrict the size of the region of the lattice in consideration. This reduction implies fewer computations and less memory space needed to carry out the dynamic programming optimization process. The observations also suggest new variants of the multiple alignment problem.

Objetivo: el presente estudio tiene como objetivo analizar el comportamiento de la producción científica sobre tres técnicas de análisis bibliométrico: la co-citación, el acoplamiento bibliográfico y la co-ocurrencia de términos. Metodología: se utiliza Web of Science como fuente de datos. Se emplean medidas de productividad e impacto para caracterizar el comportamiento de la aplicación de cada técnica. Se proponen dos nuevos índices para determinar el alcance multidisciplinar de las investigaciones, y se complementan con el análisis documental para interpretar los resultados y establecer los marcos referenciales. Resultados: se identifican los autores, instituciones y países líderes, así como la cantidad de publicaciones seriadas donde se difunden las investigaciones, y las categorías temáticas del Web of Science donde éstas están clasificadas. Se evidenció la creciente evolución de la literatura que utiliza estas técnicas para la representación y análisis de dominios del conocimiento. Los dominios tecnológicos predominaron en los núcleos temáticos de producción, aunque en los núcleos temáticos de citación también hubo presencia de los entornos biomédicos, económicos y sociales. Conclusiones: la existencia de un núcleo altamente productivo de instituciones y países evidencia la sostenida aplicación intensiva y extensiva de estas técnicas, ante el reconocimiento comunitario mundial de su importancia y validez. Los indicadores propuestos permitieron identificar el carácter multidisciplinar y la naturaleza interdisciplinar de la producción científica relacionada con estas técnicas analíticas. Además, se visibiliza la influencia de las metrías y sus técnicas al trascender los límites del dominio de conocimiento que las originó, desde propuestas teóricas y meta-teóricas hacia múltiples espacios disciplinarios.

Objective. We analyzed the scientific output after COVID-19 and contrasted it with studies published in the aftermath of seven epidemics/pandemics: Severe Acute Respiratory Syndrome (SARS), Influenza A virus H5N1 and Influenza A virus H1N1 human infections, Middle East Respiratory Syndrome (MERS), Ebola virus disease, Zika virus disease, and Dengue. Design/Methodology/Approach. We examined bibliometric measures for COVID-19 and the rest of the studied epidemics/pandemics. Data were extracted from Web of Science, using its journal classification scheme as a proxy to quantify the multidisciplinary coverage of scientific output. We proposed a novel Thematic Dispersion Index (TDI) for the analysis of pandemic early stages. Results/Discussion. The literature on the seven epidemics/pandemics before COVID-19 has shown explosive growth of the scientific production and continuous impact during the first three years following each emergence or re-emergence of the specific infectious disease. A subsequent decline was observed with the progressive control of each health emergency. We observed an unprecedented growth in COVID-19 scientific production. TDI measured for COVID-19 (29,4) in just six months, was higher than TDI of the rest (7,5 to 21) during the first three years after epidemic initiation. Conclusions. COVID-19 literature showed the broadest subject coverage, which is clearly a consequence of its social, economic, and political impact. The proposed indicator (TDI), allowed the study of multidisciplinarity, differentiating the thematic complexity of COVID-19 from the previous seven epidemics/pandemics. Originality/Value. The multidisciplinary nature and thematic complexity of COVID-19 research were successfully analyzed through a scientometric perspective.