Fast Functional Lists, Hash-Lists, Deques and Variable Length Arrays

Since its inception Functional Programming, J. McCarthy, has almost universally used the Linked List as the underpinning data structure. This paper introduces a new data structure, the VList, that is compact, thread safe and significantly faster to use than Linked Lists for nearly all list operations. Space usage can be reduced by 50% to 90% and in typical list operations speed improved by factors ranging from 4 to 20 or more. Some important operations such as indexing and length are typically changed from O(N) to O(1) and O(lgN) respectively. A language interpreter Visp, using a dialect of Common Lisp, has been implemented using VLists and the benchmark comparison with OCAML reported. It is also shown how to adapt the structure to create variable length arrays, persistent deques and functional hash tables. The VArray requires no resize copying and has an average O(1) random access time. Comparisons are made with previous resizable one dimensional arrays, Hash Array Trees (HAT) Sitarski [1996], and Brodnik, Carlsson, Demaine, Munro, and Sedgewick [1999]

NovelSNPer: A Fast Tool for the Identification and Characterization of Novel SNPs and InDels

Typically, next-generation resequencing projects produce large lists of variants. NovelSNPer is a software tool that permits fast and efficient processing of such output lists. In a first step, NovelSNPer determines if a variant represents a known variant or a previously unknown variant. In a second step, each variant is classified into one of 15 SNP classes or 19 InDel classes. Beside the classes used by Ensembl, we introduce POTENTIAL_START_GAINED and START_LOST as new functional classes and present a classification scheme for InDels. NovelSNPer is based upon the gene structure information stored in Ensembl. It processes two million SNPs in six hours. The tool can be used online or downloaded

The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures

Motivation: Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statistical viewpoint, but surprisingly few studies have investigated the relative strengths and weaknesses of the plethora of existing feature selection methods. Methods: We compare 32 feature selection methods on 4 public gene expression datasets for breast cancer prognosis, in terms of predictive performance, stability and functional interpretability of the signatures they produce. Results: We observe that the feature selection method has a significant influence on the accuracy, stability and interpretability of signatures. Simple filter methods generally outperform more complex embedded or wrapper methods, and ensemble feature selection has generally no positive effect. Overall a simple Student's t-test seems to provide the best results. Availability: Code and data are publicly available at http://cbio.ensmp.fr/~ahaury/

Lateralised sleep spindles relate to false memory generation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Sleep is known to enhance false memories: After presenting participants with lists of semantically related words, sleeping before recalling these words results in a greater acceptance of unseen “lure” words related in theme to previously seen words. Furthermore, the right hemisphere (RH) seems to be more prone to false memories than the left hemisphere (LH). In the current study, we investigated the sleep architecture associated with these false memory and lateralisation effects in a nap study. Participants viewed lists of related words, then stayed awake or slept for approximately 90 min, and were then tested for recognition of previously seen-old, unseen-new, or unseen-lure words presented either to the LH or RH. Sleep increased acceptance of unseen-lure words as previously seen compared to the wake group, particularly for RH presentations of word lists. RH lateralised stage 2 sleep spindle density relative to the LH correlated with this increase in false memories, suggesting that RH sleep spindles enhanced false memories in the RH