Preprocess and data analysis techniques for affymetrix DNA microarrays using bioconductor: a case study in Alzheimer disease

DNA microarray, or DNA chip, is a technology that allows us to obtain the expression level of many genes in a single experiment. The fact that numerical expression values can be easily obtained gives us the possibility to use multiple statistical techniques of data analysis. In this project microarray data is obtained from Gene Expression Omnibus, the repository of National Center for Biotechnology Information (NCBI). Then, the noise is removed and data is normalized, also we use hypothesis tests to find the most relevant genes that may be involved in a disease and use machine learning methods like KNN, Random Forest or Kmeans. For performing the analysis we use Bioconductor, packages in R for the analysis of biological data, and we conduct a case study in Alzheimer disease. The complete code can be found in https://github.com/alberto-poncelas/ bioc-alzheimer

Artificial fertilization of the eggs, and rearing and identification of the larvae of the anchoveta, Cetengraulis mysticetus

ENGLISH: The anchoveta, Cetengraulis mysticetus (Günther), is an important bait fish used to capture tunas in the Eastern Tropical Pacific Ocean. Contributions to the early life history of this species in the Gulf of Panama were made by Simpson (1959), who was able to identify deductively the planktonic egg of the anchoveta from 10 other anchovy eggs concurrently present. He also reared these planktonic eggs in the laboratory and described the resultant larvae to the age of 48 hours after hatching. Because of the lack of differences among the anchovy larvae, this description does not permit the identification of anchoveta larvae from those of other engraulid species. Furthermore, while adult specimens are easily recognized, up to the present it has not been possible to extend the identification of the juvenile anchoveta to specimens smaller than about 25 mm. The purpose of this study, therefore, was to identify anchoveta from the time of hatching to about 25 mm. SPANISH: La anchoveta, Cetengraulis mysticetus (Günther), es un importante pez de carnada que se emplea en la captura de los atunes en el Océano Pacífico Oriental Tropical. Simpson (1959) logró identificar deductivamente el huevo planctónico de la anchoveta al separarlo de otros diez huevos de anchoas que se encuentran al mismo tiempo, contribuyendo de esta manera a conocer los primeros estados de la historia natural de esta especie en el Golfo de Panamá. El también estableció un criadero en el laboratorio con estos huevos planctónicos y describió las larvas resultantes hasta la edad de 48 horas después de la eclosión. Debido a que no hay diferencias entre las larvas de las anchoas, esta descripción no permite identificar las larvas de la anchoveta de las otras especies de engráulidos. Más aun, a pesar de que los especímenes adultos son fácilmente reconocibles, hasta ahora no ha sido posible identificar la anchoveta juvenil de menos de unos 25 mm. Consecuentemente, el propósito del presente estudio ha sido el de identificar al anchoveta desde el momento de la eclosión hasta que tiene unos 25 mm.

Identification and estimation of size from the beaks of 18 species of cephalopods from the Pacific Ocean

A method of identifying the beaks and estimating body weight and mantle length of 18 species of cephalopods from the Pacific Ocean is presented. Twenty specimens were selected from each of the following cephalopod species: Symplectoteuthis oualaniensis, Dosidicus gigas, Ommastrephes bartramii, S. luminosa, Todarodes pacificus, Nototodarus hawaiiensis, Ornithoteuthis volalilis, Hyaloteuthis pelagica, Onychoteuthis banksii, Pterygioteuthis giardi, Abraliopsis affinis, A. felis, Liocranchia reinhardti, Leachia danae, Histioteuthis heteropsis, H. dofleini, Gonalus onyx, and Loligo opalescens. Dimensions measured on the upper and lower beak are converted to ratios and compared individually among the species using an analysis of variance procedure with Tukey's omega and Duncan's multiple range tests. Significant differences (P =0.05) observed among the species' beak ratio means and structural characteristics are used to construct artificial keys for the upper and lower beaks of the 18 species. Upper and lower beak dimensions are used as independent variables in a linear regression model with mantle length and body weight (log transformed). (PDF file contains 56 pages.)

Cooperative artificial propagation programs for salmon and steelhead, 1995-1996

Fifteen cooperative fish rearing and planting programs for salmon and steelhead were active from July 1, 1995 through June 30, 1996. For all programs, 134,213 steelhead trout,(Oncorhynchus mykiss), 7,742,577 chinook salmon,(~ tshawytscha),and 25,075 coho salmon(~ kisutch) were planted. (PDF contains 26 pages.)

Cooperative artificial propagation programs for salmon and steelhead, 1996-1997

Fourteen cooperative fish rearing and planting programs for salmon and steelhead were active from July 1, 1996 through June 30, 1997. For all programs, 208,922 steelhead trout, (Oncorhynchus mykiss), 10,334,457 chinook salmon,(O. tshawytscha),and 60,681 coho salmon(O. kisutch) were planted. (PDF contains 24 pages.)

Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression

In this paper, reanalysis fields from the ECMWF have been statistically downscaled to predict from large-scale atmospheric fields, surface moisture flux and daily precipitation at two observatories (Zaragoza and Tortosa, Ebro Valley, Spain) during the 1961-2001 period. Three types of downscaling models have been built: (i) analogues, (ii) analogues followed by random forests and (iii) analogues followed by multiple linear regression. The inputs consist of data (predictor fields) taken from the ERA-40 reanalysis. The predicted fields are precipitation and surface moisture flux as measured at the two observatories. With the aim to reduce the dimensionality of the problem, the ERA-40 fields have been decomposed using empirical orthogonal functions. Available daily data has been divided into two parts: a training period used to find a group of about 300 analogues to build the downscaling model (1961-1996) and a test period (19972001), where models' performance has been assessed using independent data. In the case of surface moisture flux, the models based on analogues followed by random forests do not clearly outperform those built on analogues plus multiple linear regression, while simple averages calculated from the nearest analogues found in the training period, yielded only slightly worse results. In the case of precipitation, the three types of model performed equally. These results suggest that most of the models' downscaling capabilities can be attributed to the analogues-calculation stage.