BioMed Research International / 2016 / Article / Tab 1

Research Article

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms

Table 1

Bacteria used in this work.

SpeciesAbbreviationNumber of essential genesNumber of total genes

Acinetobacter ADP1ACA4993307
Bacillus subtilis 168BAS2714175
Bacteroides thetaiotaomicron VPI 5482BAT3254778
Burkholderia thailandensis E264BUT4065632
Caulobacter crescentus NA1000CAC4803885
Campylobacter jejuni NCTC 11168 ATCC 700819CAJ2221572
Escherichia coli K-12 MG1655ESC2964140
Escherichia coli K-12 in PEC databaseESC_PEC2874146
Francisella novicida U112FRN3901719
Mycobacterium tuberculosis H37RvMYT6113906
Mycoplasma genitalium G37MYG378475
Mycoplasma pulmonis UAB CTIPMYP310782
Porphyromonas gingivalis ATCC 33277POG4632089
Pseudomonas aeruginosa UCBPP PA14PSA3355892
Salmonella enterica serovar Typhimurium 14028SSA14028S1055315
Salmonella enterica serovar Typhimurium LT2SAL2304451
Salmonella enterica serovar Typhimurium SL1344SAS3534446
Salmonella enterica serovar Typhi Ty2SAT3584352
Shewanella oneidensis MR 1SHO4024065
Sphingomonas wittichii RW1SPW5354850
Staphylococcus aureus N315STN3153022582
Staphylococcus aureus NCTC 8325STNCTC3462767
Streptococcus pneumonia TIGR4STT1112105
Streptococcus pneumonia R6STR1271814
Streptococcus sanguinis SK36STS2182270
Vibrio cholerae O1 biovar El Tor N16961VIC5913503

The number of essential genes and total genes are counted after filtering unmatched data.

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