http://answers.google.com/answers/threadview?id=509511
Hematology-Oncology(Heme/Onc) usually refers to the department
that sees patients with blood and platelet disorders and cancers that
are treated with a non-surgical therapy, such as bone marrow
transplant, stem cell transplant, pheresis, or chemotherapy. (Think
?liquid? therapy when differentiating heme/onc from oncology) Types of
cancer typically seen in a heme/onc department would be leukemias,
lymphomas, Hodgkins, non-Hodgkins, multiple myelomas and immunological
disorders. So, an oncologist is not a hematologist, or vice versa. But
a hematologist oncologist is a hematologist that specializes in the
diseases mentioned above. A hematologist oncologist would not treat
operable cancers such as prostate cancer.
Oncology usually refers a department that sees cancers that require
surgical treatment such as ovarian cancers, throat and digestive
system cancers, thyroid cancer, etc. Patients would be seen by an
oncologist or a surgeon with experience in cancer surgery. Some
doctors have received special training, or have experience with a
certain kind of medicine, and may see and treat patients themselves
without referring them to a specialist.
Because disorders and diseases seen in heme/onc often overlap, it is
more effective to have hematologists working closely with oncologists.
Many patients see both ?heme? and ?onc? doctors during the course of
their therapy. A breast cancer patient, for example, may be treated
with a bone marrow transplant or stem cell transplant, and her
oncologist would work in conjunction with the hematologist. Another
benefit to doctors and patients is the heme/onc clinic is equipped
with special microscopes and often have their own lab, which enables
the doctors and medical technologists to make rapid diagnosis, or
monitor patients quickly and efficiently. Hematologists and
oncologists are well trained specialists that have the skills to
identify cells under the microscope that general practice doctors
often don?t posses.
Thursday, March 11, 2010
Wednesday, March 10, 2010
Hallmarks of Cancer
http://teachercenter.insidecancer.org/browse/Hallmarks%20of%20Cancer/
Hallmarks of Cancer
o Image:Hallmarks, Overview
Hallmarks, Overview
Cancer is a disease that affects people of all nationalities and age groups and all cancers start with mutations in one cell.
o Image:Hallmarks, Growing uncontrollably
Hallmarks, Growing uncontrollably
Professor Robert Weinberg explains that cancer cells have to learn how to grow in the absence of growth stimulatory signals that normal cells require from their environment.
o Image:Hallmarks, Evading death
Hallmarks, Evading death
Professor Robert Weinberg discusses how cancer cells have to learn how to avoid the process of programmed cell death known as apoptosis carried out in normal cells.
o Image:Hallmarks, Processing nutrients
Hallmarks, Processing nutrients
Professor Robert Weinberg explains how cancer cells have to learn how to become angiogenic, that is to say attract blood vessels to grow into the tumor mass.
o Image:Hallmarks, Becoming immortal
Hallmarks, Becoming immortal
Professor Robert Weinberg explains how normal cells can only double a certain limited number of times; and cancer cells have to learn how to proliferate indefinitely, i.e, they have to become immortalized.
o Image:Hallmarks, Invading tissues
Hallmarks, Invading tissues
Professor Robert Weinberg, explains that cancer cells have to learn how to invade and metastasize.
o Image:Hallmarks, Avoiding detection
Hallmarks, Avoiding detection
Bruce Stillman, Ph.D. is president and chief executive officer of Cold Spring Harbor Laboratory, explains that there are two adaptive immune responses, and those immune responses adapt to changes in cells in our body whether they be by infection or other.
o Image:Hallmarks, Promoting mutations
Hallmarks, Promoting mutations
Bruce Stillman, Ph.D., president of Cold Spring Harbor Laboratory, explains that genomic instability is a characteristic of cancer cells.
Hallmarks of Cancer
o Image:Hallmarks, Overview
Hallmarks, Overview
Cancer is a disease that affects people of all nationalities and age groups and all cancers start with mutations in one cell.
o Image:Hallmarks, Growing uncontrollably
Hallmarks, Growing uncontrollably
Professor Robert Weinberg explains that cancer cells have to learn how to grow in the absence of growth stimulatory signals that normal cells require from their environment.
o Image:Hallmarks, Evading death
Hallmarks, Evading death
Professor Robert Weinberg discusses how cancer cells have to learn how to avoid the process of programmed cell death known as apoptosis carried out in normal cells.
o Image:Hallmarks, Processing nutrients
Hallmarks, Processing nutrients
Professor Robert Weinberg explains how cancer cells have to learn how to become angiogenic, that is to say attract blood vessels to grow into the tumor mass.
o Image:Hallmarks, Becoming immortal
Hallmarks, Becoming immortal
Professor Robert Weinberg explains how normal cells can only double a certain limited number of times; and cancer cells have to learn how to proliferate indefinitely, i.e, they have to become immortalized.
o Image:Hallmarks, Invading tissues
Hallmarks, Invading tissues
Professor Robert Weinberg, explains that cancer cells have to learn how to invade and metastasize.
o Image:Hallmarks, Avoiding detection
Hallmarks, Avoiding detection
Bruce Stillman, Ph.D. is president and chief executive officer of Cold Spring Harbor Laboratory, explains that there are two adaptive immune responses, and those immune responses adapt to changes in cells in our body whether they be by infection or other.
o Image:Hallmarks, Promoting mutations
Hallmarks, Promoting mutations
Bruce Stillman, Ph.D., president of Cold Spring Harbor Laboratory, explains that genomic instability is a characteristic of cancer cells.
P-glycoprotein
http://www.rcsb.org/pdb/static.do?p=education_discussion/molecule_of_the_month/current_month.html
they pump toxins away from the cell, including cancer drugs, so they make them less useful, and this so cancers produce more P-glycoproteins to do just this.
so we are now trying to find ways to block P-glycoprotein from ejecting the drugs from the cells.
they pump toxins away from the cell, including cancer drugs, so they make them less useful, and this so cancers produce more P-glycoproteins to do just this.
so we are now trying to find ways to block P-glycoprotein from ejecting the drugs from the cells.
Ouellette and Stein -- Changing of the guard
http://www.nature.com/nature/journal/v428/n6982/full/nj6982-584a.html
Blast in ubuntu
BLAST
http://www.ncbi.nlm.nih.gov/staff/tao/URLAPI/unix_setup.html
http://www.ncbi.nlm.nih.gov/staff/tao/URLAPI/blastdb.html
Fasta -> DB
For nucleotide: formatdb -i input_db -p F -o T
For protein: formatdb -i input_db -p T -o T
----refp_db----
>gi|113722133|ref|NP_055861.3| probable helicase senataxin [Homo sapiens]
MSTCCWCTPGGASTIDFLKRYASNTPSGEFQTADEDLCYCLECVAEYHKARDELPFLHEVLWELETLRLI
NHFEKSMKAEIGDDDELYIVDNNGEMPLFDITGQDFENKLRVPLLEILKYPYLLLHERVNELCVEALCRM
EQANCSFQVFDKHPGIYLFLVHPNEMVRRWAILTARNLGKVDRDDYYDLQEVLLCLFKVIELGLLESPDI
YTSSVLEKGKLILLPSHMYDTTNYKSYWLGICMLLTILEEQAMDSLLLGSDKQNDFMQSILHTMEREADD
DSVDPFWPALHCFMVILDRLGSKVWGQLMDPIVAFQTIINNASYNREIRHIRNSSVRTKLEPESYLDDMV
TCSQIVYNYNPEKTKKDSGWRTAICPDYCPNMYEEMETLASVLQSDIGQDMRVHNSTFLWFIPFVQSLMD
LKDLGVAYIAQVVNHLYSEVKEVLNQTDAVCDKVTEFFLLILVSVIELHRNKKCLHLLWVSSQQWVEAVV
KCAKLPTTAFTRSSEKSSGNCSKGTAMISSLSLHSMPSNSVQLAYVQLIRSLLKEGYQLGQQSLCKRFWD
KLNLFLRGNLSLGWQLTSQETHELQSCLKQIIRNIKFKAPPCNTFVDLTSACKISPASYNKEESEQMGKT
SRKDMHCLEASSPTFSKEPMKVQDSVLIKADNTIEGDNNEQNYIKDVKLEDHLLAGSCLKQSSKNIFTER
AEDQIKISTRKQKSVKEISSYTPKDCTSRNGPERGCDRGIIVSTRLLTDSSTDALEKVSTSNEDFSLKDD
ALAKTSKRKTKVQKDEICAKLSHVIKKQHRKSTLVDNTINLDENLTVSNIESFYSRKDTGVQKGDGFIHN
LSLDPSGVLDDKNGEQKSQNNVLPKEKQLKNEELVIFSFHENNCKIQEFHVDGKELIPFTEMTNASEKKS
SPFKDLMTVPESRDEEMSNSTSVIYSNLTREQAPDISPKSDTLTDSQIDRDLHKLSLLAQASVITFPSDS
PQNSSQLQRKVKEDKRCFTANQNNVGDTSRGQVIIISDSDDDDDERILSLEKLTKQDKICLEREHPEQHV
STVNSKEEKNPVKEEKTETLFQFEESDSQCFEFESSSEVFSVWQDHPDDNNSVQDGEKKCLAPIANTTNG
QGCTDYVSEVVKKGAEGIEEHTRPRSISVEEFCEIEVKKPKRKRSEKPMAEDPVRPSSSVRNEGQSDTNK
RDLVGNDFKSIDRRTSTPNSRIQRATTVSQKKSSKLCTCTEPIRKVPVSKTPKKTHSDAKKGQNRSSNYL
SCRTTPAIVPPKKFRQCPEPTSTAEKLGLKKGPRKAYELSQRSLDYVAQLRDHGKTVGVVDTRKKTKLIS
PQNLSVRNNKKLLTSQELQMQRQIRPKSQKNRRRLSDCESTDVKRAGSHTAQNSDIFVPESDRSDYNCTG
GTEVLANSNRKQLIKCMPSEPETIKAKHGSPATDDACPLNQCDSVVLNGTVPTNEVIVSTSEDPLGGGDP
TARHIEMAALKEGEPDSSSDAEEDNLFLTQNDPEDMDLCSQMENDNYKLIELIHGKDTVEVEEDSVSRPQ
LESLSGTKCKYKDCLETTKNQGEYCPKHSEVKAADEDVFRKPGLPPPASKPLRPTTKIFSSKSTSRIAGL
SKSLETSSALSPSLKNKSKGIQSILKVPQPVPLIAQKPVGEMKNSCNVLHPQSPNNSNRQGCKVPFGESK
YFPSSSPVNILLSSQSVSDTFVKEVLKWKYEMFLNFGQCGPPASLCQSISRPVPVRFHNYGDYFNVFFPL
MVLNTFETVAQEWLNSPNRENFYQLQVRKFPADYIKYWEFAVYLEECELAKQLYPKENDLVFLAPERINE
EKKDTERNDIQDLHEYHSGYVHKFRRTSVMRNGKTECYLSIQTQENFPANLNELVNCIVISSLVTTQRKL
KAMSLLGSRNQLARAVLNPNPMDFCTKDLLTTTSERIIAYLRDFNEDQKKAIETAYAMVKHSPSVAKICL
IHGPPGTGKSKTIVGLLYRLLTENQRKGHSDENSNAKIKQNRVLVCAPSNAAVDELMKKIILEFKEKCKD
KKNPLGNCGDINLVRLGPEKSINSEVLKFSLDSQVNHRMKKELPSHVQAMHKRKEFLDYQLDELSRQRAL
CRGGREIQRQELDENISKVSKERQELASKIKEVQGRPQKTQSIIILESHIICCTLSTSGGLLLESAFRGQ
GGVPFSCVIVDEAGQSCEIETLTPLIHRCNKLILVGDPKQLPPTVISMKAQEYGYDQSMMARFCRLLEEN
VEHNMISRLPILQLTVQYRMHPDICLFPSNYVYNRNLKTNRQTEAIRCSSDWPFQPYLVFDVGDGSERRD
NDSYINVQEIKLVMEIIKLIKDKRKDVSFRNIGIITHYKAQKTMIQKDLDKEFDRKGPAEVDTVDAFQGR
QKDCVIVTCVRANSIQGSIGFLASLQRLNVTITRAKYSLFILGHLRTLMENQHWNQLIQDAQKRGAIIKT
CDKNYRHDAVKILKLKPVLQRSLTHPPTIAPEGSRPQGGLPSSKLDSGFAKTSVAASLYHTPSDSKEITL
TVTSKDPERPPVHDQLQDPRLLKRMGIEVKGGIFLWDPQPSSPQHPGATPPTGEPGFPVVHQDLSHIQQP
AAVVAALSSHKPPVRGEPPAASPEASTCQSKCDDPEEELCHRREARAFSEGEQEKCGSETHHTRRNSRWD
KRTLEQEDSSSKKRKLL
>gi|187233964|gb|ACD01221.1| TP53 [Homo sapiens]
RAMAIYKQSQHMTEVVRRCPTNERCSDSDGLAPPQHLIR
>gi|119395734|ref|NP_000050.2| breast cancer type 2 susceptibility protein [Homo sapiens]
MPIGSKERPTFFEIFKTRCNKADLGPISLNWFEELSSEAPPYNSEPAEESEHKNNNYEPNLFKTPQRKPS
YNQLASTPIIFKEQGLTLPLYQSPVKELDKFKLDLGRNVPNSRHKSLRTVKTKMDQADDVSCPLLNSCLS
ESPVVLQCTHVTPQRDKSVVCGSLFHTPKFVKGRQTPKHISESLGAEVDPDMSWSSSLATPPTLSSTVLI
VRNEEASETVFPHDTTANVKSYFSNHDESLKKNDRFIASVTDSENTNQREAASHGFGKTSGNSFKVNSCK
DHIGKSMPNVLEDEVYETVVDTSEEDSFSLCFSKCRTKNLQKVRTSKTRKKIFHEANADECEKSKNQVKE
KYSFVSEVEPNDTDPLDSNVANQKPFESGSDKISKEVVPSLACEWSQLTLSGLNGAQMEKIPLLHISSCD
QNISEKDLLDTENKRKKDFLTSENSLPRISSLPKSEKPLNEETVVNKRDEEQHLESHTDCILAVKQAISG
TSPVASSFQGIKKSIFRIRESPKETFNASFSGHMTDPNFKKETEASESGLEIHTVCSQKEDSLCPNLIDN
GSWPATTTQNSVALKNAGLISTLKKKTNKFIYAIHDETSYKGKKIPKDQKSELINCSAQFEANAFEAPLT
FANADSGLLHSSVKRSCSQNDSEEPTLSLTSSFGTILRKCSRNETCSNNTVISQDLDYKEAKCNKEKLQL
FITPEADSLSCLQEGQCENDPKSKKVSDIKEEVLAAACHPVQHSKVEYSDTDFQSQKSLLYDHENASTLI
LTPTSKDVLSNLVMISRGKESYKMSDKLKGNNYESDVELTKNIPMEKNQDVCALNENYKNVELLPPEKYM
RVASPSRKVQFNQNTNLRVIQKNQEETTSISKITVNPDSEELFSDNENNFVFQVANERNNLALGNTKELH
ETDLTCVNEPIFKNSTMVLYGDTGDKQATQVSIKKDLVYVLAEENKNSVKQHIKMTLGQDLKSDISLNID
KIPEKNNDYMNKWAGLLGPISNHSFGGSFRTASNKEIKLSEHNIKKSKMFFKDIEEQYPTSLACVEIVNT
LALDNQKKLSKPQSINTVSAHLQSSVVVSDCKNSHITPQMLFSKQDFNSNHNLTPSQKAEITELSTILEE
SGSQFEFTQFRKPSYILQKSTFEVPENQMTILKTTSEECRDADLHVIMNAPSIGQVDSSKQFEGTVEIKR
KFAGLLKNDCNKSASGYLTDENEVGFRGFYSAHGTKLNVSTEALQKAVKLFSDIENISEETSAEVHPISL
SSSKCHDSVVSMFKIENHNDKTVSEKNNKCQLILQNNIEMTTGTFVEEITENYKRNTENEDNKYTAASRN
SHNLEFDGSDSSKNDTVCIHKDETDLLFTDQHNICLKLSGQFMKEGNTQIKEDLSDLTFLEVAKAQEACH
GNTSNKEQLTATKTEQNIKDFETSDTFFQTASGKNISVAKESFNKIVNFFDQKPEELHNFSLNSELHSDI
RKNKMDILSYEETDIVKHKILKESVPVGTGNQLVTFQGQPERDEKIKEPTLLGFHTASGKKVKIAKESLD
KVKNLFDEKEQGTSEITSFSHQWAKTLKYREACKDLELACETIEITAAPKCKEMQNSLNNDKNLVSIETV
VPPKLLSDNLCRQTENLKTSKSIFLKVKVHENVEKETAKSPATCYTNQSPYSVIENSALAFYTSCSRKTS
VSQTSLLEAKKWLREGIFDGQPERINTADYVGNYLYENNSNSTIAENDKNHLSEKQDTYLSNSSMSNSYS
YHSDEVYNDSGYLSKNKLDSGIEPVLKNVEDQKNTSFSKVISNVKDANAYPQTVNEDICVEELVTSSSPC
KNKNAAIKLSISNSNNFEVGPPAFRIASGKIVCVSHETIKKVKDIFTDSFSKVIKENNENKSKICQTKIM
AGCYEALDDSEDILHNSLDNDECSTHSHKVFADIQSEEILQHNQNMSGLEKVSKISPCDVSLETSDICKC
SIGKLHKSVSSANTCGIFSTASGKSVQVSDASLQNARQVFSEIEDSTKQVFSKVLFKSNEHSDQLTREEN
TAIRTPEHLISQKGFSYNVVNSSAFSGFSTASGKQVSILESSLHKVKGVLEEFDLIRTEHSLHYSPTSRQ
NVSKILPRVDKRNPEHCVNSEMEKTCSKEFKLSNNLNVEGGSSENNHSIKVSPYLSQFQQDKQQLVLGTK
VSLVENIHVLGKEQASPKNVKMEIGKTETFSDVPVKTNIEVCSTYSKDSENYFETEAVEIAKAFMEDDEL
TDSKLPSHATHSLFTCPENEEMVLSNSRIGKRRGEPLILVGEPSIKRNLLNEFDRIIENQEKSLKASKST
PDGTIKDRRLFMHHVSLEPITCVPFRTTKERQEIQNPNFTAPGQEFLSKSHLYEHLTLEKSSSNLAVSGH
PFYQVSATRNEKMRHLITTGRPTKVFVPPFKTKSHFHRVEQCVRNINLEENRQKQNIDGHGSDDSKNKIN
DNEIHQFNKNNSNQAAAVTFTKCEEEPLDLITSLQNARDIQDMRIKKKQRQRVFPQPGSLYLAKTSTLPR
ISLKAAVGGQVPSACSHKQLYTYGVSKHCIKINSKNAESFQFHTEDYFGKESLWTGKGIQLADGGWLIPS
NDGKAGKEEFYRALCDTPGVDPKLISRIWVYNHYRWIIWKLAAMECAFPKEFANRCLSPERVLLQLKYRY
DTEIDRSRRSAIKKIMERDDTAAKTLVLCVSDIISLSANISETSSNKTSSADTQKVAIIELTDGWYAVKA
QLDPPLLAVLKNGRLTVGQKIILHGAELVGSPDACTPLEAPESLMLKISANSTRPARWYTKLGFFPDPRP
FPLPLSSLFSDGGNVGCVDVIIQRAYPIQWMEKTSSGLYIFRNEREEEKEAAKYVEAQQKRLEALFTKIQ
EEFEEHEENTTKPYLPSRALTRQQVRALQDGAELYEAVKNAADPAYLEGYFSEEQLRALNNHRQMLNDKK
QAQIQLEIRKAMESAEQKEQGLSRDVTTVWKLRIVSYSKKEKDSVILSIWRPSSDLYSLLTEGKRYRIYH
LATSKSKSKSERANIQLAATKKTQYQQLPVSDEILFQIYQPREPLHFSKFLDPDFQPSCSEVDLIGFVVS
VVKKTGLAPFVYLSDECYNLLAIKFWIDLNEDIIKPHMLIAASNLQWRPESKSGLLTLFAGDFSVFSASP
KEGHFQETFNKMKNTVENIDILCNEAENKLMHILHANDPKWSTPTKDCTSGPYTAQIIPGTGNKLLMSSP
NCEIYYQSPLSLCMAKRKSVSTPVSAQMTSKSCKGEKEIDDQKNCKKRRALDFLSRLPLPPPVSPICTFV
SPAAQKAFQPPRSCGTKYETPIKKKELNSPQMTPFKKFNEISLLESNSIADEELALINTQALLSGSTGEK
QFISVSESTRTAPTSSEDYLRLKRRCTTSLIKEQESSQASTEECEKNKQDTITTKKYI
----refp_db-----
$ formatdb -i refp_db -p T -o T
----tp53.fa-----
>gi|187233964|gb|ACD01221.1| TP53 [Homo sapiens]
RAMAIYKQSQHMTEVVRRCPTNERCSDSDGLAPPQHLIR
----tp53.fa-----
$ blastall -p blastp -i tp53.fa -d refp_db
http://www.ncbi.nlm.nih.gov/staff/tao/URLAPI/unix_setup.html
http://www.ncbi.nlm.nih.gov/staff/tao/URLAPI/blastdb.html
Fasta -> DB
For nucleotide: formatdb -i input_db -p F -o T
For protein: formatdb -i input_db -p T -o T
----refp_db----
>gi|113722133|ref|NP_055861.3| probable helicase senataxin [Homo sapiens]
MSTCCWCTPGGASTIDFLKRYASNTPSGEFQTADEDLCYCLECVAEYHKARDELPFLHEVLWELETLRLI
NHFEKSMKAEIGDDDELYIVDNNGEMPLFDITGQDFENKLRVPLLEILKYPYLLLHERVNELCVEALCRM
EQANCSFQVFDKHPGIYLFLVHPNEMVRRWAILTARNLGKVDRDDYYDLQEVLLCLFKVIELGLLESPDI
YTSSVLEKGKLILLPSHMYDTTNYKSYWLGICMLLTILEEQAMDSLLLGSDKQNDFMQSILHTMEREADD
DSVDPFWPALHCFMVILDRLGSKVWGQLMDPIVAFQTIINNASYNREIRHIRNSSVRTKLEPESYLDDMV
TCSQIVYNYNPEKTKKDSGWRTAICPDYCPNMYEEMETLASVLQSDIGQDMRVHNSTFLWFIPFVQSLMD
LKDLGVAYIAQVVNHLYSEVKEVLNQTDAVCDKVTEFFLLILVSVIELHRNKKCLHLLWVSSQQWVEAVV
KCAKLPTTAFTRSSEKSSGNCSKGTAMISSLSLHSMPSNSVQLAYVQLIRSLLKEGYQLGQQSLCKRFWD
KLNLFLRGNLSLGWQLTSQETHELQSCLKQIIRNIKFKAPPCNTFVDLTSACKISPASYNKEESEQMGKT
SRKDMHCLEASSPTFSKEPMKVQDSVLIKADNTIEGDNNEQNYIKDVKLEDHLLAGSCLKQSSKNIFTER
AEDQIKISTRKQKSVKEISSYTPKDCTSRNGPERGCDRGIIVSTRLLTDSSTDALEKVSTSNEDFSLKDD
ALAKTSKRKTKVQKDEICAKLSHVIKKQHRKSTLVDNTINLDENLTVSNIESFYSRKDTGVQKGDGFIHN
LSLDPSGVLDDKNGEQKSQNNVLPKEKQLKNEELVIFSFHENNCKIQEFHVDGKELIPFTEMTNASEKKS
SPFKDLMTVPESRDEEMSNSTSVIYSNLTREQAPDISPKSDTLTDSQIDRDLHKLSLLAQASVITFPSDS
PQNSSQLQRKVKEDKRCFTANQNNVGDTSRGQVIIISDSDDDDDERILSLEKLTKQDKICLEREHPEQHV
STVNSKEEKNPVKEEKTETLFQFEESDSQCFEFESSSEVFSVWQDHPDDNNSVQDGEKKCLAPIANTTNG
QGCTDYVSEVVKKGAEGIEEHTRPRSISVEEFCEIEVKKPKRKRSEKPMAEDPVRPSSSVRNEGQSDTNK
RDLVGNDFKSIDRRTSTPNSRIQRATTVSQKKSSKLCTCTEPIRKVPVSKTPKKTHSDAKKGQNRSSNYL
SCRTTPAIVPPKKFRQCPEPTSTAEKLGLKKGPRKAYELSQRSLDYVAQLRDHGKTVGVVDTRKKTKLIS
PQNLSVRNNKKLLTSQELQMQRQIRPKSQKNRRRLSDCESTDVKRAGSHTAQNSDIFVPESDRSDYNCTG
GTEVLANSNRKQLIKCMPSEPETIKAKHGSPATDDACPLNQCDSVVLNGTVPTNEVIVSTSEDPLGGGDP
TARHIEMAALKEGEPDSSSDAEEDNLFLTQNDPEDMDLCSQMENDNYKLIELIHGKDTVEVEEDSVSRPQ
LESLSGTKCKYKDCLETTKNQGEYCPKHSEVKAADEDVFRKPGLPPPASKPLRPTTKIFSSKSTSRIAGL
SKSLETSSALSPSLKNKSKGIQSILKVPQPVPLIAQKPVGEMKNSCNVLHPQSPNNSNRQGCKVPFGESK
YFPSSSPVNILLSSQSVSDTFVKEVLKWKYEMFLNFGQCGPPASLCQSISRPVPVRFHNYGDYFNVFFPL
MVLNTFETVAQEWLNSPNRENFYQLQVRKFPADYIKYWEFAVYLEECELAKQLYPKENDLVFLAPERINE
EKKDTERNDIQDLHEYHSGYVHKFRRTSVMRNGKTECYLSIQTQENFPANLNELVNCIVISSLVTTQRKL
KAMSLLGSRNQLARAVLNPNPMDFCTKDLLTTTSERIIAYLRDFNEDQKKAIETAYAMVKHSPSVAKICL
IHGPPGTGKSKTIVGLLYRLLTENQRKGHSDENSNAKIKQNRVLVCAPSNAAVDELMKKIILEFKEKCKD
KKNPLGNCGDINLVRLGPEKSINSEVLKFSLDSQVNHRMKKELPSHVQAMHKRKEFLDYQLDELSRQRAL
CRGGREIQRQELDENISKVSKERQELASKIKEVQGRPQKTQSIIILESHIICCTLSTSGGLLLESAFRGQ
GGVPFSCVIVDEAGQSCEIETLTPLIHRCNKLILVGDPKQLPPTVISMKAQEYGYDQSMMARFCRLLEEN
VEHNMISRLPILQLTVQYRMHPDICLFPSNYVYNRNLKTNRQTEAIRCSSDWPFQPYLVFDVGDGSERRD
NDSYINVQEIKLVMEIIKLIKDKRKDVSFRNIGIITHYKAQKTMIQKDLDKEFDRKGPAEVDTVDAFQGR
QKDCVIVTCVRANSIQGSIGFLASLQRLNVTITRAKYSLFILGHLRTLMENQHWNQLIQDAQKRGAIIKT
CDKNYRHDAVKILKLKPVLQRSLTHPPTIAPEGSRPQGGLPSSKLDSGFAKTSVAASLYHTPSDSKEITL
TVTSKDPERPPVHDQLQDPRLLKRMGIEVKGGIFLWDPQPSSPQHPGATPPTGEPGFPVVHQDLSHIQQP
AAVVAALSSHKPPVRGEPPAASPEASTCQSKCDDPEEELCHRREARAFSEGEQEKCGSETHHTRRNSRWD
KRTLEQEDSSSKKRKLL
>gi|187233964|gb|ACD01221.1| TP53 [Homo sapiens]
RAMAIYKQSQHMTEVVRRCPTNERCSDSDGLAPPQHLIR
>gi|119395734|ref|NP_000050.2| breast cancer type 2 susceptibility protein [Homo sapiens]
MPIGSKERPTFFEIFKTRCNKADLGPISLNWFEELSSEAPPYNSEPAEESEHKNNNYEPNLFKTPQRKPS
YNQLASTPIIFKEQGLTLPLYQSPVKELDKFKLDLGRNVPNSRHKSLRTVKTKMDQADDVSCPLLNSCLS
ESPVVLQCTHVTPQRDKSVVCGSLFHTPKFVKGRQTPKHISESLGAEVDPDMSWSSSLATPPTLSSTVLI
VRNEEASETVFPHDTTANVKSYFSNHDESLKKNDRFIASVTDSENTNQREAASHGFGKTSGNSFKVNSCK
DHIGKSMPNVLEDEVYETVVDTSEEDSFSLCFSKCRTKNLQKVRTSKTRKKIFHEANADECEKSKNQVKE
KYSFVSEVEPNDTDPLDSNVANQKPFESGSDKISKEVVPSLACEWSQLTLSGLNGAQMEKIPLLHISSCD
QNISEKDLLDTENKRKKDFLTSENSLPRISSLPKSEKPLNEETVVNKRDEEQHLESHTDCILAVKQAISG
TSPVASSFQGIKKSIFRIRESPKETFNASFSGHMTDPNFKKETEASESGLEIHTVCSQKEDSLCPNLIDN
GSWPATTTQNSVALKNAGLISTLKKKTNKFIYAIHDETSYKGKKIPKDQKSELINCSAQFEANAFEAPLT
FANADSGLLHSSVKRSCSQNDSEEPTLSLTSSFGTILRKCSRNETCSNNTVISQDLDYKEAKCNKEKLQL
FITPEADSLSCLQEGQCENDPKSKKVSDIKEEVLAAACHPVQHSKVEYSDTDFQSQKSLLYDHENASTLI
LTPTSKDVLSNLVMISRGKESYKMSDKLKGNNYESDVELTKNIPMEKNQDVCALNENYKNVELLPPEKYM
RVASPSRKVQFNQNTNLRVIQKNQEETTSISKITVNPDSEELFSDNENNFVFQVANERNNLALGNTKELH
ETDLTCVNEPIFKNSTMVLYGDTGDKQATQVSIKKDLVYVLAEENKNSVKQHIKMTLGQDLKSDISLNID
KIPEKNNDYMNKWAGLLGPISNHSFGGSFRTASNKEIKLSEHNIKKSKMFFKDIEEQYPTSLACVEIVNT
LALDNQKKLSKPQSINTVSAHLQSSVVVSDCKNSHITPQMLFSKQDFNSNHNLTPSQKAEITELSTILEE
SGSQFEFTQFRKPSYILQKSTFEVPENQMTILKTTSEECRDADLHVIMNAPSIGQVDSSKQFEGTVEIKR
KFAGLLKNDCNKSASGYLTDENEVGFRGFYSAHGTKLNVSTEALQKAVKLFSDIENISEETSAEVHPISL
SSSKCHDSVVSMFKIENHNDKTVSEKNNKCQLILQNNIEMTTGTFVEEITENYKRNTENEDNKYTAASRN
SHNLEFDGSDSSKNDTVCIHKDETDLLFTDQHNICLKLSGQFMKEGNTQIKEDLSDLTFLEVAKAQEACH
GNTSNKEQLTATKTEQNIKDFETSDTFFQTASGKNISVAKESFNKIVNFFDQKPEELHNFSLNSELHSDI
RKNKMDILSYEETDIVKHKILKESVPVGTGNQLVTFQGQPERDEKIKEPTLLGFHTASGKKVKIAKESLD
KVKNLFDEKEQGTSEITSFSHQWAKTLKYREACKDLELACETIEITAAPKCKEMQNSLNNDKNLVSIETV
VPPKLLSDNLCRQTENLKTSKSIFLKVKVHENVEKETAKSPATCYTNQSPYSVIENSALAFYTSCSRKTS
VSQTSLLEAKKWLREGIFDGQPERINTADYVGNYLYENNSNSTIAENDKNHLSEKQDTYLSNSSMSNSYS
YHSDEVYNDSGYLSKNKLDSGIEPVLKNVEDQKNTSFSKVISNVKDANAYPQTVNEDICVEELVTSSSPC
KNKNAAIKLSISNSNNFEVGPPAFRIASGKIVCVSHETIKKVKDIFTDSFSKVIKENNENKSKICQTKIM
AGCYEALDDSEDILHNSLDNDECSTHSHKVFADIQSEEILQHNQNMSGLEKVSKISPCDVSLETSDICKC
SIGKLHKSVSSANTCGIFSTASGKSVQVSDASLQNARQVFSEIEDSTKQVFSKVLFKSNEHSDQLTREEN
TAIRTPEHLISQKGFSYNVVNSSAFSGFSTASGKQVSILESSLHKVKGVLEEFDLIRTEHSLHYSPTSRQ
NVSKILPRVDKRNPEHCVNSEMEKTCSKEFKLSNNLNVEGGSSENNHSIKVSPYLSQFQQDKQQLVLGTK
VSLVENIHVLGKEQASPKNVKMEIGKTETFSDVPVKTNIEVCSTYSKDSENYFETEAVEIAKAFMEDDEL
TDSKLPSHATHSLFTCPENEEMVLSNSRIGKRRGEPLILVGEPSIKRNLLNEFDRIIENQEKSLKASKST
PDGTIKDRRLFMHHVSLEPITCVPFRTTKERQEIQNPNFTAPGQEFLSKSHLYEHLTLEKSSSNLAVSGH
PFYQVSATRNEKMRHLITTGRPTKVFVPPFKTKSHFHRVEQCVRNINLEENRQKQNIDGHGSDDSKNKIN
DNEIHQFNKNNSNQAAAVTFTKCEEEPLDLITSLQNARDIQDMRIKKKQRQRVFPQPGSLYLAKTSTLPR
ISLKAAVGGQVPSACSHKQLYTYGVSKHCIKINSKNAESFQFHTEDYFGKESLWTGKGIQLADGGWLIPS
NDGKAGKEEFYRALCDTPGVDPKLISRIWVYNHYRWIIWKLAAMECAFPKEFANRCLSPERVLLQLKYRY
DTEIDRSRRSAIKKIMERDDTAAKTLVLCVSDIISLSANISETSSNKTSSADTQKVAIIELTDGWYAVKA
QLDPPLLAVLKNGRLTVGQKIILHGAELVGSPDACTPLEAPESLMLKISANSTRPARWYTKLGFFPDPRP
FPLPLSSLFSDGGNVGCVDVIIQRAYPIQWMEKTSSGLYIFRNEREEEKEAAKYVEAQQKRLEALFTKIQ
EEFEEHEENTTKPYLPSRALTRQQVRALQDGAELYEAVKNAADPAYLEGYFSEEQLRALNNHRQMLNDKK
QAQIQLEIRKAMESAEQKEQGLSRDVTTVWKLRIVSYSKKEKDSVILSIWRPSSDLYSLLTEGKRYRIYH
LATSKSKSKSERANIQLAATKKTQYQQLPVSDEILFQIYQPREPLHFSKFLDPDFQPSCSEVDLIGFVVS
VVKKTGLAPFVYLSDECYNLLAIKFWIDLNEDIIKPHMLIAASNLQWRPESKSGLLTLFAGDFSVFSASP
KEGHFQETFNKMKNTVENIDILCNEAENKLMHILHANDPKWSTPTKDCTSGPYTAQIIPGTGNKLLMSSP
NCEIYYQSPLSLCMAKRKSVSTPVSAQMTSKSCKGEKEIDDQKNCKKRRALDFLSRLPLPPPVSPICTFV
SPAAQKAFQPPRSCGTKYETPIKKKELNSPQMTPFKKFNEISLLESNSIADEELALINTQALLSGSTGEK
QFISVSESTRTAPTSSEDYLRLKRRCTTSLIKEQESSQASTEECEKNKQDTITTKKYI
----refp_db-----
$ formatdb -i refp_db -p T -o T
----tp53.fa-----
>gi|187233964|gb|ACD01221.1| TP53 [Homo sapiens]
RAMAIYKQSQHMTEVVRRCPTNERCSDSDGLAPPQHLIR
----tp53.fa-----
$ blastall -p blastp -i tp53.fa -d refp_db
Fix broken packages
Probably mixed ubuntu distributions, ie jaunty and intrepid
Check
$ sudo vi /etc/apt/sources.list
and remove jaunty
$ sudo apt-get install autoremove
$ sudo apt-get -f install xine-ui vlc mplayer
$ sudo apt-get build-dep mplayer meconder
Check
$ sudo vi /etc/apt/sources.list
and remove jaunty
$ sudo apt-get install autoremove
$ sudo apt-get -f install xine-ui vlc mplayer
$ sudo apt-get build-dep mplayer meconder
Monday, March 8, 2010
Quick programming reference
C++
http://www.stumbleupon.com/su/3dhSXA/www.sourcepole.com/sources/programming/cpp/cppqref.html
Perl
http://www.doulos.com/knowhow/perl/quick_start/
http://www.stumbleupon.com/su/3dhSXA/www.sourcepole.com/sources/programming/cpp/cppqref.html
Perl
http://www.doulos.com/knowhow/perl/quick_start/
Writing scalable applications
http://msdn.microsoft.com/en-us/library/ms810434.aspx
http://code.google.com/appengine/articles/scaling/overview.html
* Minimizing work - Retrieve objects/entities by key, key name, or ID, Paging results, read / write sparsely
* Paging through large datasets
* Avoiding datastore contention
* Sharding counters
* Effective memcache
http://msdn.microsoft.com/en-us/magazine/cc163854.aspx#S4
Performance on the Data Tier
Tip 1—Return Multiple Resultsets
Tip 2—Paged Data Access
Tip 3—Connection Pooling
Tip 4—ASP.NET Cache API
Tip 5—Per-Request Caching
Tip 6—Background Processing
Tip 7—Page Output Caching and Proxy Servers
Tip 8—Run IIS 6.0 (If Only for Kernel Caching)
Tip 9—Use Gzip Compression
Tip 10—Server Control View State
Conclusion
http://www.javaperformancetuning.com/tips/design.shtml#REF2
J2EE Patterns
MVC http://java.sun.com/blueprints/patterns/MVC-detailed.html
http://java.sun.com/blueprints/patterns/catalog.html
http://code.google.com/appengine/articles/scaling/overview.html
* Minimizing work - Retrieve objects/entities by key, key name, or ID, Paging results, read / write sparsely
* Paging through large datasets
* Avoiding datastore contention
* Sharding counters
* Effective memcache
http://msdn.microsoft.com/en-us/magazine/cc163854.aspx#S4
Performance on the Data Tier
Tip 1—Return Multiple Resultsets
Tip 2—Paged Data Access
Tip 3—Connection Pooling
Tip 4—ASP.NET Cache API
Tip 5—Per-Request Caching
Tip 6—Background Processing
Tip 7—Page Output Caching and Proxy Servers
Tip 8—Run IIS 6.0 (If Only for Kernel Caching)
Tip 9—Use Gzip Compression
Tip 10—Server Control View State
Conclusion
http://www.javaperformancetuning.com/tips/design.shtml#REF2
J2EE Patterns
MVC http://java.sun.com/blueprints/patterns/MVC-detailed.html
http://java.sun.com/blueprints/patterns/catalog.html
Sunday, March 7, 2010
Pokemon Top abilities
http://www.smogon.com/smog/issue4/top_abilities
480 spd-def-a Lopunny normal wk: fighting
525 sa-a Lucario fight/steel wk: fire/fighting/ground
545 sa-sd Togekiss normal/flying wk: rock / elec / ice
480 sa/a Octillery water wk: grass / elec
540 hp-sp.def-sp.a Blissey normal wk: fighting
510 def-a Gliscor ground/flying wk: ice / water
525 a-def Torterra grass/ground
480 spd Froslass ice
525 sp-a Glaceon ice
600 Garchomp dragon/ground wk: dragon/ice, special
500 sp-a Wailord water
425 sp-a chimecho psychic
http://www.youtube.com/watch?v=aFUV6N9ZIys
Battle vs Synthia
http://www.youtube.com/watch?v=S6tBB1ksgLc&feature=fvsr
Types
http://www.smogon.com/dp/types/
HM Slave - Gyrados, Bibarel, Tropius, Skarmory
http://bulbapedia.bulbagarden.net/wiki/Appendix:HM_slave
Where To Find Good Rod In Pokemon Platinum?
U can find the good rod on route 209 east from hearthome city :}
Where do you get a Super Rod on Pokemon Platinum?
Find a fisherman in the Fight Area. You need to have the National Dex. It is at the northeast exit (top left).
POKEMON PLATINUM: HOW TO GET REMORAID?
You need to fish with the Good Rod on Route 212 South, Route 213, Route 222, Route 223, Route 224, Route 230, Pastoria City, Sunyshore City, or at the Pokemon League. It is common and should be easy to catch
Hustle increases the user's Attack stat by 50%, but lowers the Accuracy of the user's Physical moves by 20%. Special moves are unaffected by Hustle.
http://www.smogon.com/dp/pokemon/octillery
Sniper multiplies the base power of an attack 1.5× during a critical hit.
List of Pokemon with Unique Type combinations
http://bulbapedia.bulbagarden.net/wiki/List_of_Pok%C3%A9mon_with_unique_type_combinations
http://bulbapedia.bulbagarden.net/wiki/Happiness
Hidden Power?
However, in Platinum, there is a man in the Veilstone Game Corner Prize Exchange house that will tell the player the type of their Pokémon's Hidden Power. In HeartGold and SoulSilver, he is present in the Celadon Game Corner Prize Exchange house
http://bulbapedia.bulbagarden.net/wiki/Hidden_Power_(move)
Honey (wait 6 1/4 hours)
http://bulbapedia.bulbagarden.net/wiki/Honey
http://wiki.answers.com/Q/What_do_you_have_to_do_when_you_have_put_honey_on_a_tree_on_pokemon_diamond
Soft reset DS
heyy! heres how to SR a DS L + R + Select + Start and .... HOLD!!
Pokemon tips / cheats
http://www.neoseeker.com/Games/cheats/DS/pokemon_platinum.html
Nature
Lonely: +attack, -defense
Brave: +attack, -speed
Adamant: +attack, -special attack
Naughty: +attack, -special defense
Bold: +defense, -attack
Relaxed: +defense, -defense
Impish: +defense, -special attack
Lax: +defense, -special defense
Timid: +speed, -attack
Hasty: +speed, -defense
Jolly: +speed, -special attack
Naive: +speed, -special defense
Modest: +special attack, -attack
Mild: +special attack, -defense
Quiet: +special attack, -speed
Rash: +special attack, -special defense
Calm: +special defense, -attack
Careful: +special defense, -special attack
Gentle: +special defense, -defense
Sassy: +special defense, -speed
Hardy: Neutral
Docile: Neutral
Serious: Neutral
Bashful: Neutral
Quirky: Neutral
obtain trade evolution pokemon
Obtain Trade-Evolution Pokemon
Pokemon such as Graveler, Haunter, Machoke, and Kadabra will only evolve when traded. You can use this trick to evolve these Pokemon using only a single DS.
Requirements:
Must have access to GTS
Must have Wi-Fi
1. Head to the GTS in Jubilife City with the Pokemon you want to evolve.
2. Deposit your Pokemon in the GTS. Request something that is IMPOSSIBLE or very rare to get, to decrease the chances of your Pokemon being traded. If your deposited Pokemon is traded, the trick will fail.
3. Seek for a Pokemon on the GTS and make any trade.
4. Once you finish the trade, withdraw the Pokemon you had deposited in the GTS. If you did the trick right, it should evolve as if it was traded.
You can do this trick with any Pokemon that is evolved through trading.
480 spd-def-a Lopunny normal wk: fighting
525 sa-a Lucario fight/steel wk: fire/fighting/ground
545 sa-sd Togekiss normal/flying wk: rock / elec / ice
480 sa/a Octillery water wk: grass / elec
540 hp-sp.def-sp.a Blissey normal wk: fighting
510 def-a Gliscor ground/flying wk: ice / water
525 a-def Torterra grass/ground
480 spd Froslass ice
525 sp-a Glaceon ice
600 Garchomp dragon/ground wk: dragon/ice, special
500 sp-a Wailord water
425 sp-a chimecho psychic
http://www.youtube.com/watch?v=aFUV6N9ZIys
Battle vs Synthia
http://www.youtube.com/watch?v=S6tBB1ksgLc&feature=fvsr
Types
http://www.smogon.com/dp/types/
HM Slave - Gyrados, Bibarel, Tropius, Skarmory
http://bulbapedia.bulbagarden.net/wiki/Appendix:HM_slave
Where To Find Good Rod In Pokemon Platinum?
U can find the good rod on route 209 east from hearthome city :}
Where do you get a Super Rod on Pokemon Platinum?
Find a fisherman in the Fight Area. You need to have the National Dex. It is at the northeast exit (top left).
POKEMON PLATINUM: HOW TO GET REMORAID?
You need to fish with the Good Rod on Route 212 South, Route 213, Route 222, Route 223, Route 224, Route 230, Pastoria City, Sunyshore City, or at the Pokemon League. It is common and should be easy to catch
Hustle increases the user's Attack stat by 50%, but lowers the Accuracy of the user's Physical moves by 20%. Special moves are unaffected by Hustle.
http://www.smogon.com/dp/pokemon/octillery
Sniper multiplies the base power of an attack 1.5× during a critical hit.
List of Pokemon with Unique Type combinations
http://bulbapedia.bulbagarden.net/wiki/List_of_Pok%C3%A9mon_with_unique_type_combinations
http://bulbapedia.bulbagarden.net/wiki/Happiness
Hidden Power?
However, in Platinum, there is a man in the Veilstone Game Corner Prize Exchange house that will tell the player the type of their Pokémon's Hidden Power. In HeartGold and SoulSilver, he is present in the Celadon Game Corner Prize Exchange house
http://bulbapedia.bulbagarden.net/wiki/Hidden_Power_(move)
Honey (wait 6 1/4 hours)
http://bulbapedia.bulbagarden.net/wiki/Honey
http://wiki.answers.com/Q/What_do_you_have_to_do_when_you_have_put_honey_on_a_tree_on_pokemon_diamond
Soft reset DS
heyy! heres how to SR a DS L + R + Select + Start and .... HOLD!!
Pokemon tips / cheats
http://www.neoseeker.com/Games/cheats/DS/pokemon_platinum.html
Nature
Lonely: +attack, -defense
Brave: +attack, -speed
Adamant: +attack, -special attack
Naughty: +attack, -special defense
Bold: +defense, -attack
Relaxed: +defense, -defense
Impish: +defense, -special attack
Lax: +defense, -special defense
Timid: +speed, -attack
Hasty: +speed, -defense
Jolly: +speed, -special attack
Naive: +speed, -special defense
Modest: +special attack, -attack
Mild: +special attack, -defense
Quiet: +special attack, -speed
Rash: +special attack, -special defense
Calm: +special defense, -attack
Careful: +special defense, -special attack
Gentle: +special defense, -defense
Sassy: +special defense, -speed
Hardy: Neutral
Docile: Neutral
Serious: Neutral
Bashful: Neutral
Quirky: Neutral
obtain trade evolution pokemon
Obtain Trade-Evolution Pokemon
Pokemon such as Graveler, Haunter, Machoke, and Kadabra will only evolve when traded. You can use this trick to evolve these Pokemon using only a single DS.
Requirements:
Must have access to GTS
Must have Wi-Fi
1. Head to the GTS in Jubilife City with the Pokemon you want to evolve.
2. Deposit your Pokemon in the GTS. Request something that is IMPOSSIBLE or very rare to get, to decrease the chances of your Pokemon being traded. If your deposited Pokemon is traded, the trick will fail.
3. Seek for a Pokemon on the GTS and make any trade.
4. Once you finish the trade, withdraw the Pokemon you had deposited in the GTS. If you did the trick right, it should evolve as if it was traded.
You can do this trick with any Pokemon that is evolved through trading.
Friday, March 5, 2010
Thursday, March 4, 2010
First Order Logic - FOL
Propositional logic is declarative but not expressive, hence we have First Order Logic (FOL), also called Predicate Calculus
Has quantifiers, universal ∀x (usually use ->), existential ∃x (usually use ^)
∃x ∀y is not the same as ∀y ∃x
∃x ∀y Loves(x,y)
“There is a person who loves everyone in the world”
∀y ∃x Loves(x,y)
“Everyone in the world is loved by at least one person”
∀x Likes(x,IceCream) = ¬∃x ¬Likes(x,IceCream)
kinship domain:
object are people
Properties include gender and they are related by relations
such as parenthood, brotherhood,marriage
predicates: Male, Female (unary)
Parent,Sibling,Daughter,Son...
Function:Mother Father
{a/Shoot} <- substitution
Has quantifiers, universal ∀x (usually use ->), existential ∃x (usually use ^)
∃x ∀y is not the same as ∀y ∃x
∃x ∀y Loves(x,y)
“There is a person who loves everyone in the world”
∀y ∃x Loves(x,y)
“Everyone in the world is loved by at least one person”
∀x Likes(x,IceCream) = ¬∃x ¬Likes(x,IceCream)
kinship domain:
object are people
Properties include gender and they are related by relations
such as parenthood, brotherhood,marriage
predicates: Male, Female (unary)
Parent,Sibling,Daughter,Son...
Function:Mother Father
{a/Shoot} <- substitution
Rule Based Reasoning
Entailment means that one thing follows from another:
KB ╞ α
Propositional Logic
--------------------
The proposition symbols P1, P2 etc are sentences
conjunction ^
disjunction V
implication (if-then) a -> b ≡ ~a V b // false iff a=T and b=F
biconditional a <-> b ≡ (a->b) ^ (b->a)
logically equivalent α ≡ ß iff α╞ β and β╞α
for:
1. (a ^ b) V (c V d)
2. (a V c V d) ^ (b V c V d)
We say we pick all the operand and operators after "a" except "^ b" since we are distributing over "^" in phrase "^ b" i.e. "a" operates on "V (c V d)" and "b" operates on the same phrase and the final operator is "^" which will go in the middle.
The same is true for the second example you mentioned...
1. (a ^ b) V (c ^ d) // Distribute over "^" in "a^b"
2. (a V (c ^ d)) ^ (b V (c ^ d)) // Expand
3. ((a V c)^(a V d)) ^ ((b V c)^(b V d)) // all operators outside parentheses are of type "^" so good to remove extra ones
4. (a V c) ^ (a V d) ^ (b V c) ^ (b V d)
A sentence is valid if it is true in all models (truth tables where α=True),
Validity is connected to inference via the Deduction Theorem:
KB ╞ α if and only if (KB ⇒ α) is valid
A sentence is satisfiable if it is true in some model
A sentence is unsatisfiable if it is true in no models
Satisfiability is connected to inference via the following:
KB ╞ α if and only if (KB ∧¬α) is unsatisfiable [] (empty clause)
Interpretation: any assignment of true and false to atoms
Rules of inference
Model checking
⌧truth table enumeration (always exponential in n)
⌧improved backtracking, e.g., Davis--Putnam-Logemann-Loveland (DPLL), Backtracking with constraint propagation, backjumping.
⌧heuristic search in model space (sound but incomplete)
e.g., min-conflicts-like hill-climbing algorithms
Resolution is sound
Resolution is NOT complete:
P and R entails P V R but you cannot infer P V R From (P and R) by resolution
Resolution is complete for refutation: adding (¬P) and (¬R) to (P and R) we can infer the empty clause. (proof by contradiction)
CNF = conjunctive normal form eg. (A V B) ^ C
( P ∧ ¬Q ) ∨ ( ¬R ∨ P ) ≡ ( P ∨ ¬ R ∨ P ) ∧ ( ¬ Q ∨ ¬R ∨ P ) ≡ ( P ∨ ¬R ), (¬Q ∨ ¬R ∨ P )
The set of support: those clauses coming from negation of the theorem or their decendents.
Horn clause: Eg C ^ (B -> A) ^ ( C ^ D -> B) NOT! (C V D -> B)
Forward chaining (data driven) - linear time
Idea: fire any rule whose premises are satisfied in the KB,
add its conclusion to the KB, until query is found
Backward chaining (goal driven) - linear time
Idea: work backwards from the query q:
to prove q by BC,
check if q is known already, or
prove by BC all premises of some rule concluding q
Avoid loops: check if new subgoal is already on the goal stack
Avoid repeated work: check if new subgoal
1. has already been proved true, or
2. has already failed
Efficient propositional inference:
- DPLL 1. early termination 2. purse symbol (same sign for everywhere, so either all nots or positives) 3. unit clause - clause with only a literal
- WalkSAT (incomplete), local search using randomness
KB ╞ α
Propositional Logic
--------------------
The proposition symbols P1, P2 etc are sentences
conjunction ^
disjunction V
implication (if-then) a -> b ≡ ~a V b // false iff a=T and b=F
biconditional a <-> b ≡ (a->b) ^ (b->a)
logically equivalent α ≡ ß iff α╞ β and β╞α
for:
1. (a ^ b) V (c V d)
2. (a V c V d) ^ (b V c V d)
We say we pick all the operand and operators after "a" except "^ b" since we are distributing over "^" in phrase "^ b" i.e. "a" operates on "V (c V d)" and "b" operates on the same phrase and the final operator is "^" which will go in the middle.
The same is true for the second example you mentioned...
1. (a ^ b) V (c ^ d) // Distribute over "^" in "a^b"
2. (a V (c ^ d)) ^ (b V (c ^ d)) // Expand
3. ((a V c)^(a V d)) ^ ((b V c)^(b V d)) // all operators outside parentheses are of type "^" so good to remove extra ones
4. (a V c) ^ (a V d) ^ (b V c) ^ (b V d)
A sentence is valid if it is true in all models (truth tables where α=True),
Validity is connected to inference via the Deduction Theorem:
KB ╞ α if and only if (KB ⇒ α) is valid
A sentence is satisfiable if it is true in some model
A sentence is unsatisfiable if it is true in no models
Satisfiability is connected to inference via the following:
KB ╞ α if and only if (KB ∧¬α) is unsatisfiable [] (empty clause)
Interpretation: any assignment of true and false to atoms
Rules of inference
Model checking
⌧truth table enumeration (always exponential in n)
⌧improved backtracking, e.g., Davis--Putnam-Logemann-Loveland (DPLL), Backtracking with constraint propagation, backjumping.
⌧heuristic search in model space (sound but incomplete)
e.g., min-conflicts-like hill-climbing algorithms
Resolution is sound
Resolution is NOT complete:
P and R entails P V R but you cannot infer P V R From (P and R) by resolution
Resolution is complete for refutation: adding (¬P) and (¬R) to (P and R) we can infer the empty clause. (proof by contradiction)
CNF = conjunctive normal form eg. (A V B) ^ C
( P ∧ ¬Q ) ∨ ( ¬R ∨ P ) ≡ ( P ∨ ¬ R ∨ P ) ∧ ( ¬ Q ∨ ¬R ∨ P ) ≡ ( P ∨ ¬R ), (¬Q ∨ ¬R ∨ P )
The set of support: those clauses coming from negation of the theorem or their decendents.
Horn clause: Eg C ^ (B -> A) ^ ( C ^ D -> B) NOT! (C V D -> B)
Forward chaining (data driven) - linear time
Idea: fire any rule whose premises are satisfied in the KB,
add its conclusion to the KB, until query is found
Backward chaining (goal driven) - linear time
Idea: work backwards from the query q:
to prove q by BC,
check if q is known already, or
prove by BC all premises of some rule concluding q
Avoid loops: check if new subgoal is already on the goal stack
Avoid repeated work: check if new subgoal
1. has already been proved true, or
2. has already failed
Efficient propositional inference:
- DPLL 1. early termination 2. purse symbol (same sign for everywhere, so either all nots or positives) 3. unit clause - clause with only a literal
- WalkSAT (incomplete), local search using randomness
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