Effective Vector Representations for Variable Length Symbol Sequences

Inspired by natural language processing techniques we here introduce Mol2vec which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Similarly, to the Word2vec models where vectors of closely related words are in close proximity in the vector space, Mol2vec learns vector representations of molecular substructures that are pointing in similar directions for chemically related substructures. Compounds can finally be encoded as vectors by summing up vectors of the individual substructures and, for instance, feed into supervised machine learning approaches to predict compound properties. The underlying substructure vector embeddings are obtained by training an unsupervised machine learning approach on a so-called corpus of compounds that consists of all available chemical matter. The resulting Mol2vec model is pre-trained once, yields dense vector representations and overcomes drawbacks of common compound feature representations such as sparseness and bit collisions. The prediction capabilities are demonstrated on several compound property and bioactivity data sets and compared with results obtained for Morgan fingerprints as reference compound representation. Mol2vec can be easily combined with ProtVec, which employs the same Word2vec concept on protein sequences, resulting in a proteochemometric approach that is alignment independent and can be thus also easily used for proteins with low sequence similarities.

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Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm

Journal of Engineering ◽

10.31026/j.eng.2018.05.05 ◽

2018 ◽

Vol 24 (5) ◽

pp. 66

Author(s):

Thamer M. Jamel ◽

Faez Fawzi Hammood

Keyword(s):

Mean Square Error ◽

Return Loss ◽

Performance Enhancement ◽

Variable Length ◽

Echo Cancellation ◽

Convergence Time ◽

Length Variation ◽

Mean Square ◽

Step Size ◽

Echo Return Loss Enhancement

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%, and 16% using Periodic, Sequential, Stochastic, and M-max PU NVLLMS algorithms respectively, compared to that used by a full update method which is very important, especially in the application of mobile communication since the power consumption must be considered. In addition, the average ERLE and average Mean Square Error (MSE) for M-max PU NVLLMS are better than other proposed algorithms.

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A Test Data Compression Scheme Based on Mixed Fixed and Variable Length Coding

Chinese Journal of Computers ◽

10.3724/sp.j.1016.2008.01826 ◽

2009 ◽

Vol 31 (10) ◽

pp. 1826-1834 ◽

Cited By ~ 1

Author(s):

Wen-Fa ZHAN ◽

Hua-Guo LIANG ◽

Feng SHI ◽

Zheng-Feng HUANG

Keyword(s):

Data Compression ◽

Test Data ◽

Variable Length ◽

Test Data Compression ◽

Compression Scheme ◽

Variable Length Coding

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Mitochondrial DNA duplication, recombination, and introgression during interspecific hybridization

Scientific Reports ◽

10.1038/s41598-021-92125-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Silvia Bágeľová Poláková ◽

Žaneta Lichtner ◽

Tomáš Szemes ◽

Martina Smolejová ◽

Pavol Sulo

Keyword(s):

Saccharomyces Cerevisiae ◽

Mitochondrial Dna ◽

Interspecific Hybridization ◽

Mobile Elements ◽

Variable Length ◽

Mitochondrial Genomes ◽

Free Standing ◽

Saccharomyces Paradoxus ◽

Mtdna Recombination

AbstractmtDNA recombination events in yeasts are known, but altered mitochondrial genomes were not completed. Therefore, we analyzed recombined mtDNAs in six Saccharomyces cerevisiae × Saccharomyces paradoxus hybrids in detail. Assembled molecules contain mostly segments with variable length introgressed to other mtDNA. All recombination sites are in the vicinity of the mobile elements, introns in cox1, cob genes and free standing ORF1, ORF4. The transplaced regions involve co-converted proximal exon regions. Thus, these selfish elements are beneficial to the host if the mother molecule is challenged with another molecule for transmission to the progeny. They trigger mtDNA recombination ensuring the transfer of adjacent regions, into the progeny of recombinant molecules. The recombination of the large segments may result in mitotically stable duplication of several genes.

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