Results 31 to 40 of about 6,337,317 (349)
Different from ribosomal genes, which contain highly conserved sequences that are detected in all- organisms, the intergenic spacer of rDNA (IGS) appears to be the most rapidly-evolving spacer region.
Mercatelli Elisabetta +3 more
doaj +1 more source
Significance Learning biological properties from sequence data is a logical step toward generative and predictive artificial intelligence for biology.
Alexander Rives +7 more
semanticscholar +1 more source
Synchronized excitability in a network enables generation of internal neuronal sequences
Hippocampal place field sequences are supported by sensory cues and network internal mechanisms. In contrast, sharp-wave (SPW) sequences, theta sequences, and episode field sequences are internally generated. The relationship of these sequences to memory
Yingxue Wang +2 more
doaj +1 more source
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome
Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of ...
Ben Langmead +3 more
semanticscholar +1 more source
Better is worse, worse is better: Reexamination of violations of dominance in intertemporal choice [PDF]
Recently, Scholten and Read (2014) found new violations of dominance in intertemporal choice. Although adding a small receipt before a delayed payment or adding a small delayed receipt after an immediate receipt makes the prospect objectively better, it ...
Cheng-Ming Jiang +5 more
doaj +3 more sources
Raw Sequences and Mapping File:Emily B. Graham, Rachel S. Gabor, Shon Schooler, Diane M. McKnight, Diana R. Nemergut, and Joseph E. Knelman. 2018. Oligotrophic wetland sediments susceptible to shifts in microbiomes and mercury cycling with dissolved ...
Emily Graham (717676)
core +2 more sources
Multiple brain regions are able to learn and express temporal sequences, and this functionality is an essential component of learning and memory. We propose a substrate for such representations via a network model that learns and recalls discrete ...
Ian Cone, Harel Z Shouval
doaj +1 more source
Sparse Sequence-to-Sequence Models [PDF]
Sequence-to-sequence models are a powerful workhorse of NLP. Most variants employ a softmax transformation in both their attention mechanism and output layer, leading to dense alignments and strictly positive output probabilities. This density is wasteful, making models less interpretable and assigning probability mass to many implausible outputs.
Ben Peters +2 more
openaire +3 more sources
SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair [PDF]
21 pages, 15 ...
Zimin Chen +5 more
openaire +3 more sources
Integrality and the Laurent phenomenon for Somos 4 and Somos 5 sequences [PDF]
Somos 4 sequences are a family of sequences defined by a fourth-order quadratic recurrence relation with constant coefficients. For particular choices of the coefficients and the four initial data, such recurrences can yield sequences of integers.
Swart, Christine, Hone, Andrew N.W.
core +1 more source

