24 research outputs found
A Deep Reinforcement Learning Based Multi-Criteria Decision Support System for Textile Manufacturing Process Optimization
Textile manufacturing is a typical traditional industry involving high
complexity in interconnected processes with limited capacity on the application
of modern technologies. Decision-making in this domain generally takes multiple
criteria into consideration, which usually arouses more complexity. To address
this issue, the present paper proposes a decision support system that combines
the intelligent data-based random forest (RF) models and a human knowledge
based analytical hierarchical process (AHP) multi-criteria structure in
accordance to the objective and the subjective factors of the textile
manufacturing process. More importantly, the textile manufacturing process is
described as the Markov decision process (MDP) paradigm, and a deep
reinforcement learning scheme, the Deep Q-networks (DQN), is employed to
optimize it. The effectiveness of this system has been validated in a case
study of optimizing a textile ozonation process, showing that it can better
master the challenging decision-making tasks in textile manufacturing
processes.Comment: arXiv admin note: text overlap with arXiv:2012.0110
Analysis of five deep-sequenced trio-genomes of the Peninsular Malaysia Orang Asli and North Borneo populations
BackgroundRecent advances in genomic technologies have facilitated genome-wide investigation of human genetic variations. However, most efforts have focused on the major populations, yet trio genomes of indigenous populations from Southeast Asia have been under-investigated.ResultsWe analyzed the whole-genome deep sequencing data (30x) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81x10(-8) - 1.33x10(-8), 1.0x10(-9) - 2.9x10(-9), and 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples.ConclusionOur study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia
Refining models of archaic admixture in Eurasia with ArchaicSeeker 2.0
We developed a method, ArchaicSeeker 2.0, to identify introgressed hominin sequences and model multiple-wave admixture. The new method enabled us to discern two waves of introgression from both Denisovan-like and Neanderthal-like hominins in present-day Eurasian populations and an ancient Siberian individual. We estimated that an early Denisovan-like introgression occurred in Eurasia around 118.8–94.0 thousand years ago (kya). In contrast, we detected only one single episode of Denisovan-like admixture in indigenous peoples eastern to the Wallace-Line. Modeling ancient admixtures suggested an early dispersal of modern humans throughout Asia before the Toba volcanic super-eruption 74 kya, predating the initial peopling of Asia as proposed by the traditional Out-of-Africa model. Survived archaic sequences are involved in various phenotypes including immune and body mass (e.g., ZNF169), cardiovascular and lung function (e.g., HHAT), UV response and carbohydrate metabolism (e.g., HYAL1/HYAL2/HYAL3), while “archaic deserts” are enriched with genes associated with skin development and keratinization
Omics Evidence: Single Nucleotide Variants Transmissions on Chromosome 20 in Liver Cancer Cell Lines
Cancer genomics unveils many cancer-related mutations, including
some chromosome 20 (Chr.20) genes. The mutated messages have been
found in the corresponding mRNAs; however, whether they could be translated
to proteins still requires more evidence. Herein, we proposed a transomics
strategy to profile the expression status of human Chr.20 genes (555
in Ensembl v72). The data of transcriptome and translatome (the mRNAs
bound with ribosome, translating mRNAs) revealed that ∼80%
of the coding genes on Chr.20 were detected with mRNA signals in three
liver cancer cell lines, whereas of the proteome identified, only
∼45% of the Chr.20 coding genes were detected. The high amount
of overlapping of identified genes in mRNA and RNC-mRNA (ribosome
nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent
distribution of the abundance averages of mRNA and RNC-mRNA along
the Chr.20 subregions in three liver cancer cell lines indicate that
the mRNA information is efficiently transmitted from transcriptional
to translational stage, qualitatively and quantitatively. Of the 457
genes identified in mRNAs and RNC-mRNA, 136 were found to contain
SNVs with 213 sites, and >40% of these SNVs existed only in metastatic
cell lines, suggesting them as the metastasis-related SNVs. Proteomics
analysis showed that 16 genes with 20 SNV sites were detected with
reliable MS/MS signals, and some SNVs were further validated by the
MRM approach. With the integration of the omics data at the three
expression phases, therefore, we are able to achieve the overall
view of the gene expression of Chr.20, which is constructive in understanding
the potential trend of encoding genes in a cell line and exploration
of a new type of markers related to cancers
Omics Evidence: Single Nucleotide Variants Transmissions on Chromosome 20 in Liver Cancer Cell Lines
Cancer genomics unveils many cancer-related mutations, including
some chromosome 20 (Chr.20) genes. The mutated messages have been
found in the corresponding mRNAs; however, whether they could be translated
to proteins still requires more evidence. Herein, we proposed a transomics
strategy to profile the expression status of human Chr.20 genes (555
in Ensembl v72). The data of transcriptome and translatome (the mRNAs
bound with ribosome, translating mRNAs) revealed that ∼80%
of the coding genes on Chr.20 were detected with mRNA signals in three
liver cancer cell lines, whereas of the proteome identified, only
∼45% of the Chr.20 coding genes were detected. The high amount
of overlapping of identified genes in mRNA and RNC-mRNA (ribosome
nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent
distribution of the abundance averages of mRNA and RNC-mRNA along
the Chr.20 subregions in three liver cancer cell lines indicate that
the mRNA information is efficiently transmitted from transcriptional
to translational stage, qualitatively and quantitatively. Of the 457
genes identified in mRNAs and RNC-mRNA, 136 were found to contain
SNVs with 213 sites, and >40% of these SNVs existed only in metastatic
cell lines, suggesting them as the metastasis-related SNVs. Proteomics
analysis showed that 16 genes with 20 SNV sites were detected with
reliable MS/MS signals, and some SNVs were further validated by the
MRM approach. With the integration of the omics data at the three
expression phases, therefore, we are able to achieve the overall
view of the gene expression of Chr.20, which is constructive in understanding
the potential trend of encoding genes in a cell line and exploration
of a new type of markers related to cancers
Omics Evidence: Single Nucleotide Variants Transmissions on Chromosome 20 in Liver Cancer Cell Lines
Cancer genomics unveils many cancer-related mutations, including
some chromosome 20 (Chr.20) genes. The mutated messages have been
found in the corresponding mRNAs; however, whether they could be translated
to proteins still requires more evidence. Herein, we proposed a transomics
strategy to profile the expression status of human Chr.20 genes (555
in Ensembl v72). The data of transcriptome and translatome (the mRNAs
bound with ribosome, translating mRNAs) revealed that ∼80%
of the coding genes on Chr.20 were detected with mRNA signals in three
liver cancer cell lines, whereas of the proteome identified, only
∼45% of the Chr.20 coding genes were detected. The high amount
of overlapping of identified genes in mRNA and RNC-mRNA (ribosome
nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent
distribution of the abundance averages of mRNA and RNC-mRNA along
the Chr.20 subregions in three liver cancer cell lines indicate that
the mRNA information is efficiently transmitted from transcriptional
to translational stage, qualitatively and quantitatively. Of the 457
genes identified in mRNAs and RNC-mRNA, 136 were found to contain
SNVs with 213 sites, and >40% of these SNVs existed only in metastatic
cell lines, suggesting them as the metastasis-related SNVs. Proteomics
analysis showed that 16 genes with 20 SNV sites were detected with
reliable MS/MS signals, and some SNVs were further validated by the
MRM approach. With the integration of the omics data at the three
expression phases, therefore, we are able to achieve the overall
view of the gene expression of Chr.20, which is constructive in understanding
the potential trend of encoding genes in a cell line and exploration
of a new type of markers related to cancers
Omics Evidence: Single Nucleotide Variants Transmissions on Chromosome 20 in Liver Cancer Cell Lines
Cancer genomics unveils many cancer-related mutations, including
some chromosome 20 (Chr.20) genes. The mutated messages have been
found in the corresponding mRNAs; however, whether they could be translated
to proteins still requires more evidence. Herein, we proposed a transomics
strategy to profile the expression status of human Chr.20 genes (555
in Ensembl v72). The data of transcriptome and translatome (the mRNAs
bound with ribosome, translating mRNAs) revealed that ∼80%
of the coding genes on Chr.20 were detected with mRNA signals in three
liver cancer cell lines, whereas of the proteome identified, only
∼45% of the Chr.20 coding genes were detected. The high amount
of overlapping of identified genes in mRNA and RNC-mRNA (ribosome
nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent
distribution of the abundance averages of mRNA and RNC-mRNA along
the Chr.20 subregions in three liver cancer cell lines indicate that
the mRNA information is efficiently transmitted from transcriptional
to translational stage, qualitatively and quantitatively. Of the 457
genes identified in mRNAs and RNC-mRNA, 136 were found to contain
SNVs with 213 sites, and >40% of these SNVs existed only in metastatic
cell lines, suggesting them as the metastasis-related SNVs. Proteomics
analysis showed that 16 genes with 20 SNV sites were detected with
reliable MS/MS signals, and some SNVs were further validated by the
MRM approach. With the integration of the omics data at the three
expression phases, therefore, we are able to achieve the overall
view of the gene expression of Chr.20, which is constructive in understanding
the potential trend of encoding genes in a cell line and exploration
of a new type of markers related to cancers