Climatic variability in Central Indian Himalaya during the last similar to 1800 years: Evidence from a high resolution speleothem record

Stable isotopes from a U/Th dated aragonite stalagmite from the Central Kumaun Himalaya provide evidence of variation in climatic conditions in the last similar to 1800 years. The delta O-18 and delta C-13 values vary from -4.3 parts per thousand to -7.6 parts per thousand and -3.4 parts per thousand to -9.1 parts per thousand respectively, although the stalagmite was not grown in isotopic equilibrium with cave drip water, a clear palaeoclimatic signal in stalagmite delta O-18 values is evident based on the regional climate data. The stalagmite showed a rapid growth rate during 830-910 AD, most likely the lower part of Medieval Warm Period (MWP), and 1600-1640 AD, the middle part of Little Ice Age (LIA). Two distinct phases of reduced precipitation are marked by a 2 parts per thousand shift in 8180 values towards the end of MWP (similar to 1080-1160 AD) and after its termination from similar to 1210 to 1440 AD. The LIA (similar to 1440-1880 AD) is represented by sub-tropical climate similar to modern conditions, whereas the post-LIA was comparatively drier. The Inter Tropical Convergence Zone (ITCZ) was located over the cave location during wetter/warmer conditions. When it shifted southward, precipitation over the study area decreased. A prominent drop in delta O-18 and delta C-13 values during the post-LIA period may also have been additionally influenced by anthropogenic activity in the area. (C) 2013 Elsevier Ltd and INQUA. All rights reserved.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.